[{"publisher":"Springer Nature","date_updated":"2023-12-13T13:09:07Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["510"],"title":"Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes","article_processing_charge":"Yes (via OA deal)","article_type":"original","status":"public","page":"675-717","date_created":"2023-10-22T22:01:14Z","year":"2023","volume":256,"scopus_import":"1","has_accepted_license":"1","abstract":[{"lang":"eng","text":"We prove the following quantitative Borsuk–Ulam-type result (an equivariant analogue of Gromov’s Topological Overlap Theorem): Let X be a free ℤ/2-complex of dimension d with coboundary expansion at least ηk in dimension 0 ≤ k < d. Then for every equivariant map F: X →ℤ/2 ℝd, the fraction of d-simplices σ of X with 0 ∈ F (σ) is at least 2−d Π d−1k=0ηk.\r\n\r\nAs an application, we show that for every sufficiently thick d-dimensional spherical building Y and every map f: Y → ℝ2d, we have f(σ) ∩ f(τ) ≠ ∅ for a constant fraction μd > 0 of pairs {σ, τ} of d-simplices of Y. In particular, such complexes are non-embeddable into ℝ2d, which proves a conjecture of Tancer and Vorwerk for sufficiently thick spherical buildings.\r\n\r\nWe complement these results by upper bounds on the coboundary expansion of two families of simplicial complexes; this indicates some limitations to the bounds one can obtain by straighforward applications of the quantitative Borsuk–Ulam theorem. Specifically, we prove\r\n\r\n• an upper bound of (d + 1)/2d on the normalized (d − 1)-th coboundary expansion constant of complete (d + 1)-partite d-dimensional complexes (under a mild divisibility assumption on the sizes of the parts); and\r\n\r\n• an upper bound of (d + 1)/2d + ε on the normalized (d − 1)-th coboundary expansion of the d-dimensional spherical building associated with GLd+2(Fq) for any ε > 0 and sufficiently large q. This disproves, in a rather strong sense, a conjecture of Lubotzky, Meshulam and Mozes."}],"citation":{"ieee":"U. Wagner and P. Wild, “Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes,” Israel Journal of Mathematics, vol. 256, no. 2. Springer Nature, pp. 675–717, 2023.","mla":"Wagner, Uli, and Pascal Wild. “Coboundary Expansion, Equivariant Overlap, and Crossing Numbers of Simplicial Complexes.” Israel Journal of Mathematics, vol. 256, no. 2, Springer Nature, 2023, pp. 675–717, doi:10.1007/s11856-023-2521-9.","ista":"Wagner U, Wild P. 2023. Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. 256(2), 675–717.","ama":"Wagner U, Wild P. Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. 2023;256(2):675-717. doi:10.1007/s11856-023-2521-9","apa":"Wagner, U., & Wild, P. (2023). Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s11856-023-2521-9","chicago":"Wagner, Uli, and Pascal Wild. “Coboundary Expansion, Equivariant Overlap, and Crossing Numbers of Simplicial Complexes.” Israel Journal of Mathematics. Springer Nature, 2023. https://doi.org/10.1007/s11856-023-2521-9.","short":"U. Wagner, P. Wild, Israel Journal of Mathematics 256 (2023) 675–717."},"isi":1,"day":"01","tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"department":[{"_id":"UlWa"}],"file":[{"file_name":"2023_IsraelJourMath_Wagner.pdf","date_updated":"2023-10-31T11:20:31Z","access_level":"open_access","checksum":"fbb05619fe4b650f341cc730425dd9c3","content_type":"application/pdf","success":1,"file_id":"14475","date_created":"2023-10-31T11:20:31Z","relation":"main_file","file_size":623787,"creator":"dernst"}],"oa_version":"Published Version","author":[{"id":"36690CA2-F248-11E8-B48F-1D18A9856A87","first_name":"Uli","last_name":"Wagner","full_name":"Wagner, Uli","orcid":"0000-0002-1494-0568"},{"full_name":"Wild, Pascal","last_name":"Wild","first_name":"Pascal","id":"4C20D868-F248-11E8-B48F-1D18A9856A87"}],"publication":"Israel Journal of Mathematics","intvolume":" 256","oa":1,"quality_controlled":"1","publication_status":"published","month":"09","external_id":{"isi":["001081646400010"]},"doi":"10.1007/s11856-023-2521-9","date_published":"2023-09-01T00:00:00Z","_id":"14445","type":"journal_article","issue":"2","file_date_updated":"2023-10-31T11:20:31Z","publication_identifier":{"issn":["0021-2172"],"eissn":["1565-8511"]},"language":[{"iso":"eng"}]},{"author":[{"full_name":"Jakubík, Jozef","last_name":"Jakubík","first_name":"Jozef"},{"first_name":"Phuong","id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","full_name":"Bui Thi Mai, Phuong","last_name":"Bui Thi Mai"},{"first_name":"Martina","full_name":"Chvosteková, Martina","last_name":"Chvosteková"},{"full_name":"Krakovská, Anna","last_name":"Krakovská","first_name":"Anna"}],"oa_version":"Published Version","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"file":[{"file_size":2639783,"creator":"dernst","file_id":"14476","date_created":"2023-10-31T12:07:23Z","relation":"main_file","date_updated":"2023-10-31T12:07:23Z","file_name":"2023_MeasurementScienceRev_Jakubik.pdf","success":1,"checksum":"b069cc10fa6a7c96b2bc9f728165f9e6","content_type":"application/pdf","access_level":"open_access"}],"department":[{"_id":"ChLa"}],"file_date_updated":"2023-10-31T12:07:23Z","publication_identifier":{"eissn":["1335-8871"]},"language":[{"iso":"eng"}],"type":"journal_article","issue":"4","quality_controlled":"1","publication_status":"published","intvolume":" 23","publication":"Measurement Science Review","oa":1,"doi":"10.2478/msr-2023-0023","date_published":"2023-08-01T00:00:00Z","_id":"14446","month":"08","page":"175-183","article_type":"original","status":"public","volume":23,"acknowledgement":"The work was supported by the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences, projects APVV-21-0216, VEGA2-0096-21 and VEGA 2-0023-22.","date_created":"2023-10-22T22:01:15Z","year":"2023","ddc":["510"],"date_updated":"2023-10-31T12:12:47Z","publisher":"Sciendo","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Against the flow of time with multi-output models","article_processing_charge":"Yes","abstract":[{"lang":"eng","text":"Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of unidirectionally coupled data. Recently, it has been shown that for unidirectionally causally connected autoregressive (AR) processes X → Y, after time reversal of data, the opposite causal direction Y → X is indeed detected, although typically as part of the bidirectional X↔ Y link. As we argue here, the answer is different when the measured data are not from AR processes but from linked deterministic systems. When the goal is the usual forward data analysis, cross-mapping-like approaches correctly detect X → Y, while Granger causality-like approaches, which should not be used for deterministic time series, detect causal independence X → Y. The results of backward causal analysis depend on the predictability of the reversed data. Unlike AR processes, observables from deterministic dynamical systems, even complex nonlinear ones, can be predicted well forward, while backward predictions can be difficult (notably when the time reversal of a function leads to one-to-many relations). To address this problem, we propose an approach based on models that provide multiple candidate predictions for the target, combined with a loss function that consideres only the best candidate. The resulting good forward and backward predictability supports the view that unidirectionally causally linked deterministic dynamical systems X → Y can be expected to detect the same link both before and after time reversal."}],"day":"01","citation":{"ieee":"J. Jakubík, M. Phuong, M. Chvosteková, and A. Krakovská, “Against the flow of time with multi-output models,” Measurement Science Review, vol. 23, no. 4. Sciendo, pp. 175–183, 2023.","mla":"Jakubík, Jozef, et al. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review, vol. 23, no. 4, Sciendo, 2023, pp. 175–83, doi:10.2478/msr-2023-0023.","chicago":"Jakubík, Jozef, Mary Phuong, Martina Chvosteková, and Anna Krakovská. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review. Sciendo, 2023. https://doi.org/10.2478/msr-2023-0023.","apa":"Jakubík, J., Phuong, M., Chvosteková, M., & Krakovská, A. (2023). Against the flow of time with multi-output models. Measurement Science Review. Sciendo. https://doi.org/10.2478/msr-2023-0023","ista":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. 2023. Against the flow of time with multi-output models. Measurement Science Review. 23(4), 175–183.","ama":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. Against the flow of time with multi-output models. Measurement Science Review. 2023;23(4):175-183. doi:10.2478/msr-2023-0023","short":"J. Jakubík, M. Phuong, M. Chvosteková, A. Krakovská, Measurement Science Review 23 (2023) 175–183."},"has_accepted_license":"1","scopus_import":"1"},{"abstract":[{"lang":"eng","text":"Auxin belongs among major phytohormones and governs multiple aspects of plant growth and development. The establishment of auxin concentration gradients, determines, among other processes, plant organ positioning and growth responses to environmental stimuli.\r\nHerein we report the synthesis of new NBD- or DNS-labelled IAA derivatives and the elucidation of their biological activity, fluorescence properties and subcellular accumulation patterns in planta. These novel compounds did not show auxin-like activity, but instead antagonized physiological auxin effects. The DNS-labelled derivatives FL5 and FL6 showed strong anti-auxin activity in roots and hypocotyls, which also occurred at the level of gene transcription as confirmed by quantitative PCR analysis. The auxin antagonism of our derivatives was further demonstrated in vitro using an SPR-based binding assay. The NBD-labelled compound FL4 with the best fluorescence properties proved to be unsuitable to study auxin accumulation patterns in planta. On the other hand, the strongest anti-auxin activity possessing compounds FL5 and FL6 could be useful to study binding mechanisms to auxin receptors and for manipulations of auxin-regulated processes."}],"citation":{"mla":"Bieleszová, Kristýna, et al. “New Fluorescent Auxin Derivatives: Anti-Auxin Activity and Accumulation Patterns in Arabidopsis Thaliana.” Plant Growth Regulation, Springer Nature, 2023, doi:10.1007/s10725-023-01083-0.","ieee":"K. Bieleszová et al., “New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana,” Plant Growth Regulation. Springer Nature, 2023.","short":"K. Bieleszová, P. Hladík, M. Kubala, R. Napier, F. Brunoni, Z. Gelová, L. Fiedler, I. Kulich, M. Strnad, K. Doležal, O. Novák, J. Friml, A. Žukauskaitė, Plant Growth Regulation (2023).","chicago":"Bieleszová, Kristýna, Pavel Hladík, Martin Kubala, Richard Napier, Federica Brunoni, Zuzana Gelová, Lukas Fiedler, et al. “New Fluorescent Auxin Derivatives: Anti-Auxin Activity and Accumulation Patterns in Arabidopsis Thaliana.” Plant Growth Regulation. Springer Nature, 2023. https://doi.org/10.1007/s10725-023-01083-0.","ama":"Bieleszová K, Hladík P, Kubala M, et al. New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation. 2023. doi:10.1007/s10725-023-01083-0","apa":"Bieleszová, K., Hladík, P., Kubala, M., Napier, R., Brunoni, F., Gelová, Z., … Žukauskaitė, A. (2023). New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation. Springer Nature. https://doi.org/10.1007/s10725-023-01083-0","ista":"Bieleszová K, Hladík P, Kubala M, Napier R, Brunoni F, Gelová Z, Fiedler L, Kulich I, Strnad M, Doležal K, Novák O, Friml J, Žukauskaitė A. 2023. New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation."},"day":"13","isi":1,"scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s10725-023-01083-0"}],"article_type":"original","status":"public","date_created":"2023-10-22T22:01:15Z","year":"2023","acknowledgement":"The authors would like to thank Karolína Kubiasová and Iñigo Saiz-Fernández for valuable scientific discussions. Open access publishing supported by the National Technical Library in Prague. This work was supported by the Palacký University Olomouc Young Researcher Grant Competition (JG_2020_002), by the Internal Grant Agency of Palacký University Olomouc (IGA_PrF_2023_016, IGA_PrF_2023_031), by the Ministry of Education, Youth and Sports of the Czech Republic through the European Regional Development Fund-Project Plants as a tool for sustainable global development (CZ.02.1.01/0.0/0.0/16_019/0000827) and the project Support of mobility at Palacký University Olomouc II. (CZ.02.2.69/0.0/0.0/18_053/0016919). The Biacore T200 SPR instrument was provided by the WISB Research Technology Facility within the School of Life Sciences, University of Warwick.","publisher":"Springer Nature","date_updated":"2023-12-13T13:08:25Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana","article_processing_charge":"Yes (via OA deal)","type":"journal_article","language":[{"iso":"eng"}],"publication_identifier":{"eissn":["1573-5087"],"issn":["0167-6903"]},"publication":"Plant Growth Regulation","oa":1,"quality_controlled":"1","publication_status":"epub_ahead","month":"10","external_id":{"isi":["001084334300001"]},"date_published":"2023-10-13T00:00:00Z","doi":"10.1007/s10725-023-01083-0","_id":"14447","author":[{"first_name":"Kristýna","last_name":"Bieleszová","full_name":"Bieleszová, Kristýna"},{"first_name":"Pavel","last_name":"Hladík","full_name":"Hladík, Pavel"},{"first_name":"Martin","full_name":"Kubala, Martin","last_name":"Kubala"},{"first_name":"Richard","full_name":"Napier, Richard","last_name":"Napier"},{"first_name":"Federica","last_name":"Brunoni","full_name":"Brunoni, Federica"},{"last_name":"Gelová","orcid":"0000-0003-4783-1752","full_name":"Gelová, Zuzana","id":"0AE74790-0E0B-11E9-ABC7-1ACFE5697425","first_name":"Zuzana"},{"last_name":"Fiedler","full_name":"Fiedler, Lukas","id":"7c417475-8972-11ed-ae7b-8b674ca26986","first_name":"Lukas"},{"last_name":"Kulich","full_name":"Kulich, Ivan","id":"57a1567c-8314-11eb-9063-c9ddc3451a54","first_name":"Ivan"},{"first_name":"Miroslav","full_name":"Strnad, Miroslav","last_name":"Strnad"},{"first_name":"Karel","full_name":"Doležal, Karel","last_name":"Doležal"},{"last_name":"Novák","full_name":"Novák, Ondřej","first_name":"Ondřej"},{"orcid":"0000-0002-8302-7596","full_name":"Friml, Jiří","last_name":"Friml","first_name":"Jiří","id":"4159519E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Asta","last_name":"Žukauskaitė","full_name":"Žukauskaitė, Asta"}],"oa_version":"Published Version","department":[{"_id":"JiFr"}]},{"page":"11980-11989","status":"public","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2010.09567","open_access":"1"}],"volume":2023,"year":"2023","date_created":"2023-10-22T22:01:16Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"IEEE","date_updated":"2023-10-31T12:01:24Z","article_processing_charge":"No","title":"Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions","abstract":[{"lang":"eng","text":"We consider the problem of solving LP relaxations of MAP-MRF inference problems, and in particular the method proposed recently in [16], [35]. As a key computational subroutine, it uses a variant of the Frank-Wolfe (FW) method to minimize a smooth convex function over a combinatorial polytope. We propose an efficient implementation of this subroutine based on in-face Frank-Wolfe directions, introduced in [4] in a different context. More generally, we define an abstract data structure for a combinatorial subproblem that enables in-face FW directions, and describe its specialization for tree-structured MAP-MRF inference subproblems. Experimental results indicate that the resulting method is the current state-of-art LP solver for some classes of problems. Our code is available at pub.ist.ac.at/~vnk/papers/IN-FACE-FW.html."}],"day":"22","citation":{"short":"V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 11980–11989.","ama":"Kolmogorov V. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol 2023. IEEE; 2023:11980-11989. doi:10.1109/CVPR52729.2023.01153","ista":"Kolmogorov V. 2023. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition vol. 2023, 11980–11989.","apa":"Kolmogorov, V. (2023). Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2023, pp. 11980–11989). Vancouver, Canada: IEEE. https://doi.org/10.1109/CVPR52729.2023.01153","chicago":"Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2023:11980–89. IEEE, 2023. https://doi.org/10.1109/CVPR52729.2023.01153.","mla":"Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2023, IEEE, 2023, pp. 11980–89, doi:10.1109/CVPR52729.2023.01153.","ieee":"V. Kolmogorov, “Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, 2023, vol. 2023, pp. 11980–11989."},"scopus_import":"1","author":[{"first_name":"Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","full_name":"Kolmogorov, Vladimir","last_name":"Kolmogorov"}],"oa_version":"Preprint","department":[{"_id":"VlKo"}],"publication_identifier":{"issn":["1063-6919"],"isbn":["9798350301298"]},"language":[{"iso":"eng"}],"type":"conference","publication_status":"published","quality_controlled":"1","oa":1,"intvolume":" 2023","publication":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","_id":"14448","doi":"10.1109/CVPR52729.2023.01153","date_published":"2023-08-22T00:00:00Z","external_id":{"arxiv":["2010.09567"]},"arxiv":1,"conference":{"name":"CVPR: Conference on Computer Vision and Pattern Recognition","start_date":"2023-06-17","end_date":"2023-06-24","location":"Vancouver, Canada"},"month":"08"},{"pmid":1,"title":"Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action","article_processing_charge":"Yes","article_number":"1257002","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-12-13T13:07:21Z","publisher":"Frontiers","ddc":["000"],"date_created":"2023-10-22T22:01:16Z","year":"2023","volume":14,"acknowledgement":"This study is based upon work from COST Action ML4Microbiome “Statistical and machine learning techniques in human microbiome studies” (CA18131), supported by COST (European Cooperation in Science and Technology), www.cost.eu. MB acknowledges support through the Metagenopolis grant ANR-11-DPBS-0001. IM-I acknowledges support by the “Miguel Servet Type II” program (CPII21/00013) of the ISCIII-Madrid (Spain), co-financed by the FEDER.\r\nThe authors are grateful to all COST Action CA18131 “Statistical and machine learning techniques in human microbiome studies” members for their contribution to the COST Action objectives, and to COST (European Cooperation in Science and Technology) for the economic support, www.cost.eu. WG2 and WG3 thank Emmanuelle Le Chatelier and Pauline Barbet (Université Paris-Saclay, INRAE, MetaGenoPolis, 78350, Jouy-en-Josas, France) for preparing the shotgun CRC benchmark dataset.","article_type":"original","status":"public","scopus_import":"1","has_accepted_license":"1","citation":{"ista":"D’Elia D, Truu J, Lahti L, Berland M, Papoutsoglou G, Ceci M, Zomer A, Lopes MB, Ibrahimi E, Gruca A, Nechyporenko A, Frohme M, Klammsteiner T, Pau ECDS, Marcos-Zambrano LJ, Hron K, Pio G, Simeon A, Suharoschi R, Moreno-Indias I, Temko A, Nedyalkova M, Apostol ES, Truică CO, Shigdel R, Telalović JH, Bongcam-Rudloff E, Przymus P, Jordamović NB, Falquet L, Tarazona S, Sampri A, Isola G, Pérez-Serrano D, Trajkovik V, Klucar L, Loncar-Turukalo T, Havulinna AS, Jansen C, Bertelsen RJ, Claesson MJ. 2023. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. 14, 1257002.","apa":"D’Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M., … Claesson, M. J. (2023). Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. Frontiers. https://doi.org/10.3389/fmicb.2023.1257002","chicago":"D’Elia, Domenica, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology. Frontiers, 2023. https://doi.org/10.3389/fmicb.2023.1257002.","ama":"D’Elia D, Truu J, Lahti L, et al. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. 2023;14. doi:10.3389/fmicb.2023.1257002","short":"D. D’Elia, J. Truu, L. Lahti, M. Berland, G. Papoutsoglou, M. Ceci, A. Zomer, M.B. Lopes, E. Ibrahimi, A. Gruca, A. Nechyporenko, M. Frohme, T. Klammsteiner, E.C.D.S. Pau, L.J. Marcos-Zambrano, K. Hron, G. Pio, A. Simeon, R. Suharoschi, I. Moreno-Indias, A. Temko, M. Nedyalkova, E.S. Apostol, C.O. Truică, R. Shigdel, J.H. Telalović, E. Bongcam-Rudloff, P. Przymus, N.B. Jordamović, L. Falquet, S. Tarazona, A. Sampri, G. Isola, D. Pérez-Serrano, V. Trajkovik, L. Klucar, T. Loncar-Turukalo, A.S. Havulinna, C. Jansen, R.J. Bertelsen, M.J. Claesson, Frontiers in Microbiology 14 (2023).","ieee":"D. D’Elia et al., “Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action,” Frontiers in Microbiology, vol. 14. Frontiers, 2023.","mla":"D’Elia, Domenica, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology, vol. 14, 1257002, Frontiers, 2023, doi:10.3389/fmicb.2023.1257002."},"isi":1,"day":"25","abstract":[{"text":"The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.","lang":"eng"}],"department":[{"_id":"ScienComp"}],"file":[{"file_id":"14471","relation":"main_file","date_created":"2023-10-30T13:38:48Z","creator":"dernst","file_size":505078,"date_updated":"2023-10-30T13:38:48Z","file_name":"2023_FrontiersMicrobiology_DElia.pdf","success":1,"access_level":"open_access","content_type":"application/pdf","checksum":"6c0acdd8fa111a699826957b8dff19d5"}],"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"author":[{"first_name":"Domenica","last_name":"D’Elia","full_name":"D’Elia, Domenica"},{"full_name":"Truu, Jaak","last_name":"Truu","first_name":"Jaak"},{"full_name":"Lahti, Leo","last_name":"Lahti","first_name":"Leo"},{"first_name":"Magali","full_name":"Berland, Magali","last_name":"Berland"},{"last_name":"Papoutsoglou","full_name":"Papoutsoglou, Georgios","first_name":"Georgios"},{"first_name":"Michelangelo","full_name":"Ceci, Michelangelo","last_name":"Ceci"},{"first_name":"Aldert","last_name":"Zomer","full_name":"Zomer, Aldert"},{"full_name":"Lopes, Marta B.","last_name":"Lopes","first_name":"Marta B."},{"last_name":"Ibrahimi","full_name":"Ibrahimi, Eliana","first_name":"Eliana"},{"first_name":"Aleksandra","full_name":"Gruca, Aleksandra","last_name":"Gruca"},{"last_name":"Nechyporenko","full_name":"Nechyporenko, Alina","first_name":"Alina"},{"first_name":"Marcus","last_name":"Frohme","full_name":"Frohme, Marcus"},{"first_name":"Thomas","last_name":"Klammsteiner","full_name":"Klammsteiner, Thomas"},{"first_name":"Enrique Carrillo De Santa","last_name":"Pau","full_name":"Pau, Enrique Carrillo De Santa"},{"first_name":"Laura Judith","last_name":"Marcos-Zambrano","full_name":"Marcos-Zambrano, Laura Judith"},{"first_name":"Karel","full_name":"Hron, Karel","last_name":"Hron"},{"first_name":"Gianvito","last_name":"Pio","full_name":"Pio, Gianvito"},{"first_name":"Andrea","full_name":"Simeon, Andrea","last_name":"Simeon"},{"full_name":"Suharoschi, Ramona","last_name":"Suharoschi","first_name":"Ramona"},{"full_name":"Moreno-Indias, Isabel","last_name":"Moreno-Indias","first_name":"Isabel"},{"full_name":"Temko, Andriy","last_name":"Temko","first_name":"Andriy"},{"last_name":"Nedyalkova","full_name":"Nedyalkova, Miroslava","first_name":"Miroslava"},{"first_name":"Elena Simona","full_name":"Apostol, Elena Simona","last_name":"Apostol"},{"full_name":"Truică, Ciprian Octavian","last_name":"Truică","first_name":"Ciprian Octavian"},{"first_name":"Rajesh","last_name":"Shigdel","full_name":"Shigdel, Rajesh"},{"first_name":"Jasminka Hasić","last_name":"Telalović","full_name":"Telalović, Jasminka Hasić"},{"full_name":"Bongcam-Rudloff, Erik","last_name":"Bongcam-Rudloff","first_name":"Erik"},{"first_name":"Piotr","full_name":"Przymus, Piotr","last_name":"Przymus"},{"full_name":"Jordamović, Naida Babić","last_name":"Jordamović","first_name":"Naida Babić"},{"first_name":"Laurent","full_name":"Falquet, Laurent","last_name":"Falquet"},{"last_name":"Tarazona","full_name":"Tarazona, Sonia","first_name":"Sonia"},{"last_name":"Sampri","full_name":"Sampri, Alexia","first_name":"Alexia"},{"first_name":"Gaetano","full_name":"Isola, Gaetano","last_name":"Isola"},{"first_name":"David","last_name":"Pérez-Serrano","full_name":"Pérez-Serrano, David"},{"last_name":"Trajkovik","full_name":"Trajkovik, Vladimir","first_name":"Vladimir"},{"first_name":"Lubos","last_name":"Klucar","full_name":"Klucar, Lubos"},{"first_name":"Tatjana","last_name":"Loncar-Turukalo","full_name":"Loncar-Turukalo, Tatjana"},{"last_name":"Havulinna","full_name":"Havulinna, Aki S.","first_name":"Aki S."},{"last_name":"Jansen","full_name":"Jansen, Christian","id":"837b2259-bcc9-11ed-a196-ae55927bc6e2","first_name":"Christian"},{"full_name":"Bertelsen, Randi J.","last_name":"Bertelsen","first_name":"Randi J."},{"first_name":"Marcus Joakim","last_name":"Claesson","full_name":"Claesson, Marcus Joakim"}],"oa_version":"Published Version","month":"09","external_id":{"isi":["001080536000001"],"pmid":["37808321"]},"date_published":"2023-09-25T00:00:00Z","doi":"10.3389/fmicb.2023.1257002","_id":"14449","oa":1,"intvolume":" 14","publication":"Frontiers in Microbiology","quality_controlled":"1","publication_status":"published","type":"journal_article","file_date_updated":"2023-10-30T13:38:48Z","publication_identifier":{"eissn":["1664-302X"]},"language":[{"iso":"eng"}]},{"publication_identifier":{"eissn":["1433-3058"],"issn":["0941-0643"]},"language":[{"iso":"eng"}],"type":"journal_article","quality_controlled":"1","publication_status":"epub_ahead","oa":1,"publication":"Neural Computing and Applications","doi":"10.1007/s00521-023-09033-7","date_published":"2023-10-05T00:00:00Z","_id":"14451","month":"10","arxiv":1,"external_id":{"arxiv":["2203.04579"]},"oa_version":"Published Version","author":[{"last_name":"Cornalba","orcid":"0000-0002-6269-5149","full_name":"Cornalba, Federico","id":"2CEB641C-A400-11E9-A717-D712E6697425","first_name":"Federico"},{"last_name":"Disselkamp","full_name":"Disselkamp, Constantin","first_name":"Constantin"},{"last_name":"Scassola","full_name":"Scassola, Davide","first_name":"Davide"},{"first_name":"Christopher","full_name":"Helf, Christopher","last_name":"Helf"}],"department":[{"_id":"JuFi"}],"ec_funded":1,"abstract":[{"lang":"eng","text":"We investigate the potential of Multi-Objective, Deep Reinforcement Learning for stock and cryptocurrency single-asset trading: in particular, we consider a Multi-Objective algorithm which generalizes the reward functions and discount factor (i.e., these components are not specified a priori, but incorporated in the learning process). Firstly, using several important assets (BTCUSD, ETHUSDT, XRPUSDT, AAPL, SPY, NIFTY50), we verify the reward generalization property of the proposed Multi-Objective algorithm, and provide preliminary statistical evidence showing increased predictive stability over the corresponding Single-Objective strategy. Secondly, we show that the Multi-Objective algorithm has a clear edge over the corresponding Single-Objective strategy when the reward mechanism is sparse (i.e., when non-null feedback is infrequent over time). Finally, we discuss the generalization properties with respect to the discount factor. The entirety of our code is provided in open-source format."}],"day":"05","citation":{"mla":"Cornalba, Federico, et al. “Multi-Objective Reward Generalization: Improving Performance of Deep Reinforcement Learning for Applications in Single-Asset Trading.” Neural Computing and Applications, Springer Nature, 2023, doi:10.1007/s00521-023-09033-7.","ieee":"F. Cornalba, C. Disselkamp, D. Scassola, and C. Helf, “Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading,” Neural Computing and Applications. Springer Nature, 2023.","short":"F. Cornalba, C. Disselkamp, D. Scassola, C. Helf, Neural Computing and Applications (2023).","ista":"Cornalba F, Disselkamp C, Scassola D, Helf C. 2023. Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications.","chicago":"Cornalba, Federico, Constantin Disselkamp, Davide Scassola, and Christopher Helf. “Multi-Objective Reward Generalization: Improving Performance of Deep Reinforcement Learning for Applications in Single-Asset Trading.” Neural Computing and Applications. Springer Nature, 2023. https://doi.org/10.1007/s00521-023-09033-7.","apa":"Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2023). Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. Springer Nature. https://doi.org/10.1007/s00521-023-09033-7","ama":"Cornalba F, Disselkamp C, Scassola D, Helf C. Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. 2023. doi:10.1007/s00521-023-09033-7"},"scopus_import":"1","main_file_link":[{"url":"https://doi.org/10.1007/s00521-023-09033-7","open_access":"1"}],"article_type":"original","project":[{"grant_number":"F6504","_id":"fc31cba2-9c52-11eb-aca3-ff467d239cd2","name":"Taming Complexity in Partial Differential Systems"},{"grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships"}],"status":"public","acknowledgement":"Open access funding provided by Università degli Studi di Trieste within the CRUI-CARE Agreement. Funding was provided by Austrian Science Fund (Grant No. F65), Horizon 2020 (Grant No. 754411) and Österreichische Forschungsförderungsgesellschaft.","date_created":"2023-10-22T22:01:16Z","year":"2023","publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-10-31T10:58:28Z","title":"Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading","article_processing_charge":"Yes (via OA deal)"},{"day":"01","citation":{"mla":"Barton, Nicholas H., et al. “The Infinitesimal Model with Dominance.” Genetics, vol. 225, no. 2, iyad133, Oxford Academic, 2023, doi:10.1093/genetics/iyad133.","ieee":"N. H. Barton, A. M. Etheridge, and A. Véber, “The infinitesimal model with dominance,” Genetics, vol. 225, no. 2. Oxford Academic, 2023.","short":"N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).","ama":"Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics. 2023;225(2). doi:10.1093/genetics/iyad133","chicago":"Barton, Nicholas H, Alison M. Etheridge, and Amandine Véber. “The Infinitesimal Model with Dominance.” Genetics. Oxford Academic, 2023. https://doi.org/10.1093/genetics/iyad133.","apa":"Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133","ista":"Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance. Genetics. 225(2), iyad133."},"abstract":[{"lang":"eng","text":"The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and an environmental component, and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents’ trait values, and has a variance that is independent of the parental traits. In previous work, we showed that when trait values are determined by the sum of a large number of additive Mendelian factors, each of small effect, one can justify the infinitesimal model as a limit of Mendelian inheritance. In this paper, we show that this result extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. Now, with just first-order dominance effects, we require two-, three-, and four-way identities. We also show that, even if we condition on parental trait values, the “shared” and “residual” components of trait values within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/M−−√. We illustrate our results with some numerical examples."}],"related_material":{"record":[{"status":"public","relation":"research_data","id":"12949"}]},"has_accepted_license":"1","scopus_import":"1","volume":225,"acknowledgement":"NHB was supported in part by ERC Grants 250152 and 101055327. AV was partly supported by the chaire Modélisation Mathématique et Biodiversité of Veolia Environment—Ecole Polytechnique—Museum National d’Histoire Naturelle—Fondation X.","date_created":"2023-10-29T23:01:15Z","year":"2023","article_type":"original","status":"public","project":[{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"},{"grant_number":"101055327","_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00","name":"Understanding the evolution of continuous genomes"}],"article_number":"iyad133","title":"The infinitesimal model with dominance","article_processing_charge":"Yes (in subscription journal)","ddc":["570"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Oxford Academic","date_updated":"2025-05-28T11:42:48Z","file_date_updated":"2023-10-30T12:57:53Z","publication_identifier":{"issn":["0016-6731"],"eissn":["1943-2631"]},"language":[{"iso":"eng"}],"type":"journal_article","issue":"2","doi":"10.1093/genetics/iyad133","date_published":"2023-10-01T00:00:00Z","_id":"14452","month":"10","arxiv":1,"external_id":{"arxiv":["2211.03515"]},"quality_controlled":"1","publication_status":"published","oa":1,"publication":"Genetics","intvolume":" 225","oa_version":"Published Version","author":[{"first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton"},{"first_name":"Alison M.","last_name":"Etheridge","full_name":"Etheridge, Alison M."},{"first_name":"Amandine","last_name":"Véber","full_name":"Véber, Amandine"}],"file":[{"date_updated":"2023-10-30T12:57:53Z","file_name":"2023_Genetics_Barton.pdf","access_level":"open_access","content_type":"application/pdf","checksum":"3f65b1fbe813e2f4dbb5d2b5e891844a","success":1,"relation":"main_file","file_id":"14469","date_created":"2023-10-30T12:57:53Z","file_size":1439032,"creator":"dernst"}],"department":[{"_id":"NiBa"}],"ec_funded":1,"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"}},{"has_accepted_license":"1","scopus_import":"1","abstract":[{"text":"Squall lines are substantially influenced by the interaction of low-level shear with cold pools associated with convective downdrafts. Beyond an optimal shear amplitude, squall lines tend to orient themselves at an angle with respect to the low-level shear. While the mechanisms behind squall line orientation seem to be increasingly well understood, uncertainties remain on the implications of this orientation. Roca and Fiolleau (2020, https://doi.org/10.1038/s43247-020-00015-4) show that long lived mesoscale convective systems, including squall lines, are disproportionately involved in rainfall extremes in the tropics. This article investigates the influence of the interaction between low-level shear and squall line outflow on squall line generated precipitation extrema in the tropics. Using a cloud resolving model, simulated squall lines in radiative convective equilibrium amid a shear-dominated regime (super optimal), a balanced regime (optimal), and an outflow dominated regime (suboptimal). Our results show that precipitation extremes in squall lines are 40% more intense in the case of optimal shear and remain 30% superior in the superoptimal regime relative to a disorganized case. With a theoretical scaling of precipitation extremes (C. Muller & Takayabu, 2020, https://doi.org/10.1088/1748-9326/ab7130), we show that the condensation rates control the amplification of precipitation extremes in tropical squall lines, mainly due to its change in vertical mass flux (dynamic component). The reduction of dilution by entrainment explains half of this change, consistent with Mulholland et al. (2021, https://doi.org/10.1175/jas-d-20-0299.1). The other half is explained by increased cloud-base velocity intensity in optimal and superoptimal squall lines.","lang":"eng"}],"isi":1,"day":"01","citation":{"ieee":"S. Abramian, C. J. Muller, and C. Risi, “Extreme precipitation in tropical squall lines,” Journal of Advances in Modeling Earth Systems, vol. 15, no. 10. Wiley, 2023.","mla":"Abramian, Sophie, et al. “Extreme Precipitation in Tropical Squall Lines.” Journal of Advances in Modeling Earth Systems, vol. 15, no. 10, e2022MS003477, Wiley, 2023, doi:10.1029/2022MS003477.","ama":"Abramian S, Muller CJ, Risi C. Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. 2023;15(10). doi:10.1029/2022MS003477","apa":"Abramian, S., Muller, C. J., & Risi, C. (2023). Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. Wiley. https://doi.org/10.1029/2022MS003477","chicago":"Abramian, Sophie, Caroline J Muller, and Camille Risi. “Extreme Precipitation in Tropical Squall Lines.” Journal of Advances in Modeling Earth Systems. Wiley, 2023. https://doi.org/10.1029/2022MS003477.","ista":"Abramian S, Muller CJ, Risi C. 2023. Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. 15(10), e2022MS003477.","short":"S. Abramian, C.J. Muller, C. Risi, Journal of Advances in Modeling Earth Systems 15 (2023)."},"ddc":["550"],"publisher":"Wiley","date_updated":"2023-12-13T13:06:40Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"e2022MS003477","title":"Extreme precipitation in tropical squall lines","article_processing_charge":"Yes","article_type":"original","status":"public","project":[{"_id":"629205d8-2b32-11ec-9570-e1356ff73576","grant_number":"805041","name":"organization of CLoUdS, and implications of Tropical cyclones and for the Energetics of the tropics, in current and waRming climate","call_identifier":"H2020"}],"volume":15,"acknowledgement":"The authors gratefully acknowledge funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (Project CLUSTER, Grant Agreement No. 805041). This work is also supported by a PhD fellowship funded by the Ecole Normale Supérieure de Paris-Saclay. Authors are also grateful to Benjamin Filider, who was of great help and support in the development of ideas. Eventually, we would like to thank Martin Singh, John M. Peters and an anonymous reviewer for their valuable comments and suggestions, which greatly improved the quality of the manuscript.","date_created":"2023-10-29T23:01:15Z","year":"2023","quality_controlled":"1","publication_status":"published","publication":"Journal of Advances in Modeling Earth Systems","intvolume":" 15","oa":1,"date_published":"2023-10-01T00:00:00Z","doi":"10.1029/2022MS003477","_id":"14453","month":"10","external_id":{"isi":["001084933600001"]},"publication_identifier":{"eissn":["1942-2466"]},"file_date_updated":"2023-10-30T13:31:42Z","language":[{"iso":"eng"}],"type":"journal_article","issue":"10","tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"file":[{"file_name":"2023_JAMES_Abramian.pdf","date_updated":"2023-10-30T13:31:42Z","checksum":"43e6a1a35b663843c7d3f8d0caaca1a5","content_type":"application/pdf","access_level":"open_access","success":1,"creator":"dernst","file_size":1975210,"date_created":"2023-10-30T13:31:42Z","file_id":"14470","relation":"main_file"}],"department":[{"_id":"CaMu"}],"ec_funded":1,"author":[{"full_name":"Abramian, Sophie","last_name":"Abramian","first_name":"Sophie"},{"last_name":"Muller","orcid":"0000-0001-5836-5350","full_name":"Muller, Caroline J","id":"f978ccb0-3f7f-11eb-b193-b0e2bd13182b","first_name":"Caroline J"},{"full_name":"Risi, Camille","last_name":"Risi","first_name":"Camille"}],"oa_version":"Published Version"},{"scopus_import":"1","citation":{"mla":"Henzinger, Thomas A., et al. “Monitoring Algorithmic Fairness under Partial Observations.” 23rd International Conference on Runtime Verification, vol. 14245, Springer Nature, 2023, pp. 291–311, doi:10.1007/978-3-031-44267-4_15.","ieee":"T. A. Henzinger, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness under partial observations,” in 23rd International Conference on Runtime Verification, Thessaloniki, Greece, 2023, vol. 14245, pp. 291–311.","short":"T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference on Runtime Verification, Springer Nature, 2023, pp. 291–311.","ista":"Henzinger TA, Kueffner K, Mallik K. 2023. Monitoring algorithmic fairness under partial observations. 23rd International Conference on Runtime Verification. RV: Conference on Runtime Verification, LNCS, vol. 14245, 291–311.","apa":"Henzinger, T. A., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic fairness under partial observations. In 23rd International Conference on Runtime Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature. https://doi.org/10.1007/978-3-031-44267-4_15","chicago":"Henzinger, Thomas A, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness under Partial Observations.” In 23rd International Conference on Runtime Verification, 14245:291–311. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_15.","ama":"Henzinger TA, Kueffner K, Mallik K. Monitoring algorithmic fairness under partial observations. In: 23rd International Conference on Runtime Verification. Vol 14245. Springer Nature; 2023:291-311. doi:10.1007/978-3-031-44267-4_15"},"day":"01","abstract":[{"lang":"eng","text":"As AI and machine-learned software are used increasingly for making decisions that affect humans, it is imperative that they remain fair and unbiased in their decisions. To complement design-time bias mitigation measures, runtime verification techniques have been introduced recently to monitor the algorithmic fairness of deployed systems. Previous monitoring techniques assume full observability of the states of the (unknown) monitored system. Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events. In this work, we extend fairness monitoring to systems modeled as partially observed Markov chains (POMC), and to specifications containing arithmetic expressions over the expected values of numerical functions on event sequences. The only assumptions we make are that the underlying POMC is aperiodic and starts in the stationary distribution, with a bound on its mixing time being known. These assumptions enable us to estimate a given property for the entire distribution of possible executions of the monitored POMC, by observing only a single execution. Our monitors observe a long run of the system and, after each new observation, output updated PAC-estimates of how fair or biased the system is. The monitors are computationally lightweight and, using a prototype implementation, we demonstrate their effectiveness on several real-world examples."}],"article_processing_charge":"No","title":"Monitoring algorithmic fairness under partial observations","date_updated":"2023-10-31T11:48:20Z","publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2023","date_created":"2023-10-29T23:01:15Z","acknowledgement":"This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.","volume":14245,"status":"public","project":[{"name":"Vigilant Algorithmic Monitoring of Software","call_identifier":"H2020","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","grant_number":"101020093"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2308.00341"}],"page":"291-311","external_id":{"arxiv":["2308.00341"]},"arxiv":1,"conference":{"location":"Thessaloniki, Greece","end_date":"2023-10-06","start_date":"2023-10-03","name":"RV: Conference on Runtime Verification"},"month":"10","_id":"14454","date_published":"2023-10-01T00:00:00Z","doi":"10.1007/978-3-031-44267-4_15","intvolume":" 14245","oa":1,"publication":"23rd International Conference on Runtime Verification","publication_status":"published","quality_controlled":"1","alternative_title":["LNCS"],"type":"conference","publication_identifier":{"isbn":["9783031442667"],"eissn":["1611-3349"],"issn":["0302-9743"]},"language":[{"iso":"eng"}],"ec_funded":1,"department":[{"_id":"ToHe"}],"author":[{"full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Kueffner","full_name":"Kueffner, Konstantin","orcid":"0000-0001-8974-2542","id":"8121a2d0-dc85-11ea-9058-af578f3b4515","first_name":"Konstantin"},{"id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","first_name":"Kaushik","last_name":"Mallik","full_name":"Mallik, Kaushik","orcid":"0000-0001-9864-7475"}],"oa_version":"Preprint"},{"volume":14,"acknowledgement":"The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work has been partially supported by Italian Ministry of Health Grant RC2023 (and the 5 × 1,000 voluntary contributions). The authors thank the children and their families with whom they work daily.","date_created":"2023-10-29T23:01:16Z","year":"2023","article_type":"letter_note","status":"public","article_number":"1287879","pmid":1,"title":"Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment","article_processing_charge":"Yes","ddc":["570"],"date_updated":"2023-12-13T13:06:07Z","publisher":"Frontiers","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"03","isi":1,"citation":{"ista":"Narzisi A, Halladay A, Masi G, Novarino G, Lord C. 2023. Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. 14, 1287879.","chicago":"Narzisi, Antonio, Alycia Halladay, Gabriele Masi, Gaia Novarino, and Catherine Lord. “Tempering Expectations: Considerations on the Current State of Stem Cells Therapy for Autism Treatment.” Frontiers in Psychiatry. Frontiers, 2023. https://doi.org/10.3389/fpsyt.2023.1287879.","apa":"Narzisi, A., Halladay, A., Masi, G., Novarino, G., & Lord, C. (2023). Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. Frontiers. https://doi.org/10.3389/fpsyt.2023.1287879","ama":"Narzisi A, Halladay A, Masi G, Novarino G, Lord C. Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. 2023;14. doi:10.3389/fpsyt.2023.1287879","short":"A. Narzisi, A. Halladay, G. Masi, G. Novarino, C. Lord, Frontiers in Psychiatry 14 (2023).","ieee":"A. Narzisi, A. Halladay, G. Masi, G. Novarino, and C. Lord, “Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment,” Frontiers in Psychiatry, vol. 14. Frontiers, 2023.","mla":"Narzisi, Antonio, et al. “Tempering Expectations: Considerations on the Current State of Stem Cells Therapy for Autism Treatment.” Frontiers in Psychiatry, vol. 14, 1287879, Frontiers, 2023, doi:10.3389/fpsyt.2023.1287879."},"has_accepted_license":"1","scopus_import":"1","oa_version":"Published Version","author":[{"last_name":"Narzisi","full_name":"Narzisi, Antonio","first_name":"Antonio"},{"first_name":"Alycia","last_name":"Halladay","full_name":"Halladay, Alycia"},{"first_name":"Gabriele","full_name":"Masi, Gabriele","last_name":"Masi"},{"last_name":"Novarino","full_name":"Novarino, Gaia","orcid":"0000-0002-7673-7178","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","first_name":"Gaia"},{"first_name":"Catherine","full_name":"Lord, Catherine","last_name":"Lord"}],"file":[{"date_created":"2023-10-30T12:48:40Z","file_id":"14468","relation":"main_file","file_size":147878,"creator":"dernst","success":1,"content_type":"application/pdf","checksum":"0a76373e9a4c0fc199f80380de257e86","access_level":"open_access","date_updated":"2023-10-30T12:48:40Z","file_name":"2023_FrontiersPsychiatry_Narzisi.pdf"}],"department":[{"_id":"GaNo"}],"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"publication_identifier":{"eissn":["1664-0640"]},"file_date_updated":"2023-10-30T12:48:40Z","language":[{"iso":"eng"}],"type":"journal_article","doi":"10.3389/fpsyt.2023.1287879","date_published":"2023-10-03T00:00:00Z","_id":"14455","month":"10","external_id":{"isi":["001084841700001"],"pmid":["37854442"]},"quality_controlled":"1","publication_status":"published","publication":"Frontiers in Psychiatry","oa":1,"intvolume":" 14"},{"day":"21","citation":{"ieee":"J. M. Křišťan and J. Svoboda, “Shortest dominating set reconfiguration under token sliding,” in 24th International Symposium on Fundamentals of Computation Theory, Trier, Germany, 2023, vol. 14292, pp. 333–347.","mla":"Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration under Token Sliding.” 24th International Symposium on Fundamentals of Computation Theory, vol. 14292, Springer Nature, 2023, pp. 333–47, doi:10.1007/978-3-031-43587-4_24.","chicago":"Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration under Token Sliding.” In 24th International Symposium on Fundamentals of Computation Theory, 14292:333–47. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-43587-4_24.","ama":"Křišťan JM, Svoboda J. Shortest dominating set reconfiguration under token sliding. In: 24th International Symposium on Fundamentals of Computation Theory. Vol 14292. Springer Nature; 2023:333-347. doi:10.1007/978-3-031-43587-4_24","ista":"Křišťan JM, Svoboda J. 2023. Shortest dominating set reconfiguration under token sliding. 24th International Symposium on Fundamentals of Computation Theory. FCT: Fundamentals of Computation Theory, LNCS, vol. 14292, 333–347.","apa":"Křišťan, J. M., & Svoboda, J. (2023). Shortest dominating set reconfiguration under token sliding. In 24th International Symposium on Fundamentals of Computation Theory (Vol. 14292, pp. 333–347). Trier, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-43587-4_24","short":"J.M. Křišťan, J. Svoboda, in:, 24th International Symposium on Fundamentals of Computation Theory, Springer Nature, 2023, pp. 333–347."},"abstract":[{"text":"In this paper, we present novel algorithms that efficiently compute a shortest reconfiguration sequence between two given dominating sets in trees and interval graphs under the TOKEN SLIDING model. In this problem, a graph is provided along with its two dominating sets, which can be imagined as tokens placed on vertices. The objective is to find a shortest sequence of dominating sets that transforms one set into the other, with each set in the sequence resulting from sliding a single token in the previous set. While identifying any sequence has been well studied, our work presents the first polynomial algorithms for this optimization variant in the context of dominating sets.","lang":"eng"}],"related_material":{"link":[{"relation":"erratum","url":"https://doi.org/10.1007/978-3-031-43587-4_31"}]},"scopus_import":"1","volume":14292,"date_created":"2023-10-29T23:01:16Z","year":"2023","page":"333-347","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2307.10847"}],"status":"public","title":"Shortest dominating set reconfiguration under token sliding","article_processing_charge":"No","date_updated":"2024-01-22T08:10:49Z","publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","alternative_title":["LNCS"],"language":[{"iso":"eng"}],"publication_identifier":{"isbn":["9783031435867"],"eissn":["1611-3349"],"issn":["0302-9743"]},"type":"conference","date_published":"2023-09-21T00:00:00Z","doi":"10.1007/978-3-031-43587-4_24","_id":"14456","month":"09","external_id":{"arxiv":["2307.10847"]},"arxiv":1,"conference":{"location":"Trier, Germany","end_date":"2023-09-21","start_date":"2023-09-18","name":"FCT: Fundamentals of Computation Theory"},"quality_controlled":"1","publication_status":"published","intvolume":" 14292","oa":1,"publication":"24th International Symposium on Fundamentals of Computation Theory","oa_version":"Preprint","author":[{"first_name":"Jan Matyáš","full_name":"Křišťan, Jan Matyáš","last_name":"Křišťan"},{"id":"130759D2-D7DD-11E9-87D2-DE0DE6697425","first_name":"Jakub","last_name":"Svoboda","full_name":"Svoboda, Jakub","orcid":"0000-0002-1419-3267"}],"department":[{"_id":"KrCh"}]},{"page":"215-228","status":"public","main_file_link":[{"open_access":"1","url":"https://eprint.iacr.org/2023/1017"}],"volume":14168,"year":"2023","date_created":"2023-10-29T23:01:16Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-10-31T11:43:12Z","publisher":"Springer Nature","article_processing_charge":"No","title":"Stronger lower bounds for leakage-resilient secret sharing","abstract":[{"text":"Threshold secret sharing allows a dealer to split a secret s into n shares, such that any t shares allow for reconstructing s, but no t-1 shares reveal any information about s. Leakage-resilient secret sharing requires that the secret remains hidden, even when an adversary additionally obtains a limited amount of leakage from every share. Benhamouda et al. (CRYPTO’18) proved that Shamir’s secret sharing scheme is one bit leakage-resilient for reconstruction threshold t≥0.85n and conjectured that the same holds for t = c.n for any constant 0≤c≤1. Nielsen and Simkin (EUROCRYPT’20) showed that this is the best one can hope for by proving that Shamir’s scheme is not secure against one-bit leakage when t0c.n/log(n).\r\nIn this work, we strengthen the lower bound of Nielsen and Simkin. We consider noisy leakage-resilience, where a random subset of leakages is replaced by uniformly random noise. We prove a lower bound for Shamir’s secret sharing, similar to that of Nielsen and Simkin, which holds even when a constant fraction of leakages is replaced by random noise. To this end, we first prove a lower bound on the share size of any noisy-leakage-resilient sharing scheme. We then use this lower bound to show that there exist universal constants c1, c2, such that for sufficiently large n it holds that Shamir’s secret sharing scheme is not noisy-leakage-resilient for t≤c1.n/log(n), even when a c2 fraction of leakages are replaced by random noise.\r\n\r\n\r\n\r\n","lang":"eng"}],"day":"01","citation":{"chicago":"Hoffmann, Charlotte, and Mark Simkin. “Stronger Lower Bounds for Leakage-Resilient Secret Sharing.” In 8th International Conference on Cryptology and Information Security in Latin America, 14168:215–28. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44469-2_11.","ista":"Hoffmann C, Simkin M. 2023. Stronger lower bounds for leakage-resilient secret sharing. 8th International Conference on Cryptology and Information Security in Latin America. LATINCRYPT: Conference on Cryptology and Information Security in Latin America, LNCS, vol. 14168, 215–228.","apa":"Hoffmann, C., & Simkin, M. (2023). Stronger lower bounds for leakage-resilient secret sharing. In 8th International Conference on Cryptology and Information Security in Latin America (Vol. 14168, pp. 215–228). Quito, Ecuador: Springer Nature. https://doi.org/10.1007/978-3-031-44469-2_11","ama":"Hoffmann C, Simkin M. Stronger lower bounds for leakage-resilient secret sharing. In: 8th International Conference on Cryptology and Information Security in Latin America. Vol 14168. Springer Nature; 2023:215-228. doi:10.1007/978-3-031-44469-2_11","short":"C. Hoffmann, M. Simkin, in:, 8th International Conference on Cryptology and Information Security in Latin America, Springer Nature, 2023, pp. 215–228.","ieee":"C. Hoffmann and M. Simkin, “Stronger lower bounds for leakage-resilient secret sharing,” in 8th International Conference on Cryptology and Information Security in Latin America, Quito, Ecuador, 2023, vol. 14168, pp. 215–228.","mla":"Hoffmann, Charlotte, and Mark Simkin. “Stronger Lower Bounds for Leakage-Resilient Secret Sharing.” 8th International Conference on Cryptology and Information Security in Latin America, vol. 14168, Springer Nature, 2023, pp. 215–28, doi:10.1007/978-3-031-44469-2_11."},"scopus_import":"1","oa_version":"Preprint","author":[{"last_name":"Hoffmann","full_name":"Hoffmann, Charlotte","orcid":"0000-0003-2027-5549","id":"0f78d746-dc7d-11ea-9b2f-83f92091afe7","first_name":"Charlotte"},{"first_name":"Mark","full_name":"Simkin, Mark","last_name":"Simkin"}],"department":[{"_id":"KrPi"}],"publication_identifier":{"issn":["0302-9743"],"eissn":["1611-3349"],"isbn":["9783031444685"]},"language":[{"iso":"eng"}],"type":"conference","alternative_title":["LNCS"],"publication_status":"published","quality_controlled":"1","oa":1,"publication":"8th International Conference on Cryptology and Information Security in Latin America","intvolume":" 14168","_id":"14457","doi":"10.1007/978-3-031-44469-2_11","date_published":"2023-10-01T00:00:00Z","conference":{"location":"Quito, Ecuador","end_date":"2023-10-06","name":"LATINCRYPT: Conference on Cryptology and Information Security in Latin America","start_date":"2023-10-03"},"month":"10"},{"date_updated":"2023-10-31T09:59:42Z","publisher":"ML Research Press","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"SparseGPT: Massive language models can be accurately pruned in one-shot","article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2301.00774","open_access":"1"}],"status":"public","project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"page":"10323-10337","date_created":"2023-10-29T23:01:16Z","year":"2023","volume":202,"acknowledgement":"The authors gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 programme (grant agreement No. 805223 ScaleML), as well as experimental support from Eldar Kurtic, and from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl.","scopus_import":"1","abstract":[{"text":"We show for the first time that large-scale generative pretrained transformer (GPT) family models can be pruned to at least 50% sparsity in one-shot, without any retraining, at minimal loss of accuracy. This is achieved via a new pruning method called SparseGPT, specifically designed to work efficiently and accurately on massive GPT-family models. We can execute SparseGPT on the largest available open-source models, OPT-175B and BLOOM-176B, in under 4.5 hours, and can reach 60% unstructured sparsity with negligible increase in perplexity: remarkably, more than 100 billion weights from these models can be ignored at inference time. SparseGPT generalizes to semi-structured (2:4 and 4:8) patterns, and is compatible with weight quantization approaches. The code is available at: https://github.com/IST-DASLab/sparsegpt.","lang":"eng"}],"citation":{"ama":"Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.","ista":"Frantar E, Alistarh D-A. 2023. SparseGPT: Massive language models can be accurately pruned in one-shot. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 10323–10337.","apa":"Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models can be accurately pruned in one-shot. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii, HI, United States: ML Research Press.","chicago":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.","short":"E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.","ieee":"E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.","mla":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37."},"day":"30","department":[{"_id":"DaAl"}],"ec_funded":1,"oa_version":"Preprint","author":[{"first_name":"Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","full_name":"Frantar, Elias","last_name":"Frantar"},{"full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"intvolume":" 202","publication":"Proceedings of the 40th International Conference on Machine Learning","oa":1,"quality_controlled":"1","publication_status":"published","month":"07","conference":{"location":"Honolulu, Hawaii, HI, United States","end_date":"2023-07-29","name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23"},"external_id":{"arxiv":["2301.00774"]},"arxiv":1,"date_published":"2023-07-30T00:00:00Z","_id":"14458","type":"conference","language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2640-3498"]},"acknowledged_ssus":[{"_id":"ScienComp"}],"alternative_title":["PMLR"]},{"alternative_title":["PMLR"],"type":"conference","publication_identifier":{"eissn":["2640-3498"]},"language":[{"iso":"eng"}],"month":"07","conference":{"name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23","end_date":"2023-07-29","location":"Honolulu, Hawaii, HI, United States"},"external_id":{"arxiv":["2212.13468"]},"arxiv":1,"date_published":"2023-07-30T00:00:00Z","_id":"14459","publication":"Proceedings of the 40th International Conference on Machine Learning","intvolume":" 202","oa":1,"quality_controlled":"1","publication_status":"published","oa_version":"Preprint","author":[{"first_name":"Aleksandr","id":"F2B06EC2-C99E-11E9-89F0-752EE6697425","full_name":"Shevchenko, Aleksandr","last_name":"Shevchenko"},{"last_name":"Kögler","full_name":"Kögler, Kevin","id":"94ec913c-dc85-11ea-9058-e5051ab2428b","first_name":"Kevin"},{"full_name":"Hassani, Hamed","last_name":"Hassani","first_name":"Hamed"},{"orcid":"0000-0002-3242-7020","full_name":"Mondelli, Marco","last_name":"Mondelli","first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425"}],"department":[{"_id":"MaMo"},{"_id":"DaAl"}],"citation":{"short":"A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.","apa":"Shevchenko, A., Kögler, K., Hassani, H., & Mondelli, M. (2023). Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.","chicago":"Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.","ama":"Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.","ista":"Shevchenko A, Kögler K, Hassani H, Mondelli M. 2023. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 31151–31209.","mla":"Shevchenko, Aleksandr, et al. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 31151–209.","ieee":"A. Shevchenko, K. Kögler, H. Hassani, and M. Mondelli, “Fundamental limits of two-layer autoencoders, and achieving them with gradient methods,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 31151–31209."},"day":"30","abstract":[{"text":"Autoencoders are a popular model in many branches of machine learning and lossy data compression. However, their fundamental limits, the performance of gradient methods and the features learnt during optimization remain poorly understood, even in the two-layer setting. In fact, earlier work has considered either linear autoencoders or specific training regimes (leading to vanishing or diverging compression rates). Our paper addresses this gap by focusing on non-linear two-layer autoencoders trained in the challenging proportional regime in which the input dimension scales linearly with the size of the representation. Our results characterize the minimizers of the population risk, and show that such minimizers are achieved by gradient methods; their structure is also unveiled, thus leading to a concise description of the features obtained via training. For the special case of a sign activation function, our analysis establishes the fundamental limits for the lossy compression of Gaussian sources via (shallow) autoencoders. Finally, while the results are proved for Gaussian data, numerical simulations on standard datasets display the universality of the theoretical predictions.","lang":"eng"}],"scopus_import":"1","date_created":"2023-10-29T23:01:17Z","year":"2023","volume":202,"acknowledgement":"Aleksandr Shevchenko, Kevin Kogler and Marco Mondelli are supported by the 2019 Lopez-Loreta Prize. Hamed Hassani acknowledges the support by the NSF CIF award (1910056) and the NSF Institute for CORE Emerging Methods in Data Science (EnCORE).","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2212.13468"}],"status":"public","project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"page":"31151-31209","title":"Fundamental limits of two-layer autoencoders, and achieving them with gradient methods","article_processing_charge":"No","date_updated":"2024-09-10T13:03:19Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"ML Research Press"},{"oa_version":"Preprint","author":[{"first_name":"Mahdi","id":"66374281-f394-11eb-9cf6-869147deecc0","full_name":"Nikdan, Mahdi","last_name":"Nikdan"},{"first_name":"Tommaso","full_name":"Pegolotti, Tommaso","last_name":"Pegolotti"},{"last_name":"Iofinova","full_name":"Iofinova, Eugenia B","orcid":"0000-0002-7778-3221","id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","first_name":"Eugenia B"},{"last_name":"Kurtic","full_name":"Kurtic, Eldar","id":"47beb3a5-07b5-11eb-9b87-b108ec578218","first_name":"Eldar"},{"orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"ec_funded":1,"department":[{"_id":"DaAl"}],"alternative_title":["PMLR"],"type":"conference","language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2640-3498"]},"external_id":{"arxiv":["2302.04852"]},"conference":{"location":"Honolulu, Hawaii, HI, United States","end_date":"2023-07-29","name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23"},"arxiv":1,"month":"07","_id":"14460","date_published":"2023-07-30T00:00:00Z","publication":"Proceedings of the 40th International Conference on Machine Learning","oa":1,"intvolume":" 202","publication_status":"published","quality_controlled":"1","year":"2023","date_created":"2023-10-29T23:01:17Z","acknowledgement":"We would like to thank Elias Frantar for his valuable assistance and support at the outset of this project, and the anonymous ICML and SNN reviewers for very constructive feedback. EI was supported in part by the FWF DK VGSCO, grant agreement number W1260-N35. DA acknowledges generous ERC support, via Starting Grant 805223 ScaleML. ","volume":202,"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"status":"public","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2302.04852"}],"page":"26215-26227","article_processing_charge":"No","title":"SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"ML Research Press","date_updated":"2023-10-31T09:33:51Z","citation":{"short":"M. Nikdan, T. Pegolotti, E.B. Iofinova, E. Kurtic, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 26215–26227.","chicago":"Nikdan, Mahdi, Tommaso Pegolotti, Eugenia B Iofinova, Eldar Kurtic, and Dan-Adrian Alistarh. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” In Proceedings of the 40th International Conference on Machine Learning, 202:26215–27. ML Research Press, 2023.","apa":"Nikdan, M., Pegolotti, T., Iofinova, E. B., Kurtic, E., & Alistarh, D.-A. (2023). SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 26215–26227). Honolulu, Hawaii, HI, United States: ML Research Press.","ista":"Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. 2023. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 26215–26227.","ama":"Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.","mla":"Nikdan, Mahdi, et al. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 26215–27.","ieee":"M. Nikdan, T. Pegolotti, E. B. Iofinova, E. Kurtic, and D.-A. Alistarh, “SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 26215–26227."},"day":"30","abstract":[{"lang":"eng","text":"We provide an efficient implementation of the backpropagation algorithm, specialized to the case where the weights of the neural network being trained are sparse. Our algorithm is general, as it applies to arbitrary (unstructured) sparsity and common layer types (e.g., convolutional or linear). We provide a fast vectorized implementation on commodity CPUs, and show that it can yield speedups in end-to-end runtime experiments, both in transfer learning using already-sparsified networks, and in training sparse networks from scratch. Thus, our results provide the first support for sparse training on commodity hardware."}],"scopus_import":"1"},{"title":"Quantized distributed training of large models with convergence guarantees","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-10-31T09:40:45Z","publisher":"ML Research Press","volume":202,"acknowledgement":"The authors gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), as well as experimental support from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl. AV acknowledges the support of the French Agence Nationale de la Recherche (ANR), under grant ANR-21-CE48-0016 (project COMCOPT), the support of Fondation Hadamard with a PRMO grant, and the support of CNRS with a CoopIntEER IEA grant (project ALFRED).","date_created":"2023-10-29T23:01:17Z","year":"2023","page":"24020-24044","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2302.02390","open_access":"1"}],"project":[{"call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"status":"public","scopus_import":"1","day":"30","citation":{"mla":"Markov, Ilia, et al. “Quantized Distributed Training of Large Models with Convergence Guarantees.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 24020–44.","ieee":"I. Markov, A. Vladu, Q. Guo, and D.-A. Alistarh, “Quantized distributed training of large models with convergence guarantees,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 24020–24044.","short":"I. Markov, A. Vladu, Q. Guo, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 24020–24044.","apa":"Markov, I., Vladu, A., Guo, Q., & Alistarh, D.-A. (2023). Quantized distributed training of large models with convergence guarantees. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 24020–24044). Honolulu, Hawaii, HI, United States: ML Research Press.","ista":"Markov I, Vladu A, Guo Q, Alistarh D-A. 2023. Quantized distributed training of large models with convergence guarantees. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 24020–24044.","chicago":"Markov, Ilia, Adrian Vladu, Qi Guo, and Dan-Adrian Alistarh. “Quantized Distributed Training of Large Models with Convergence Guarantees.” In Proceedings of the 40th International Conference on Machine Learning, 202:24020–44. ML Research Press, 2023.","ama":"Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044."},"abstract":[{"text":"Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs). The recent emergence of large language models such as GPT has created the need for new approaches to exploit data-parallelism. Among these, fully-sharded data parallel (FSDP) training is highly popular, yet it still encounters scalability bottlenecks. One reason is that applying compression techniques to FSDP is challenging: as the vast majority of the communication involves the model’s weights, direct compression alters convergence and leads to accuracy loss. We present QSDP, a variant of FSDP which supports both gradient and weight quantization with theoretical guarantees, is simple to implement and has essentially no overheads. To derive QSDP we prove that a natural modification of SGD achieves convergence even when we only maintain quantized weights, and thus the domain over which we train consists of quantized points and is, therefore, highly non-convex. We validate this approach by training GPT-family models with up to 1.3 billion parameters on a multi-node cluster. Experiments show that QSDP preserves model accuracy, while completely removing the communication bottlenecks of FSDP, providing end-to-end speedups of up to 2.2x.","lang":"eng"}],"department":[{"_id":"DaAl"}],"ec_funded":1,"oa_version":"Preprint","author":[{"id":"D0CF4148-C985-11E9-8066-0BDEE5697425","first_name":"Ilia","last_name":"Markov","full_name":"Markov, Ilia"},{"first_name":"Adrian","full_name":"Vladu, Adrian","last_name":"Vladu"},{"first_name":"Qi","last_name":"Guo","full_name":"Guo, Qi"},{"orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"date_published":"2023-07-30T00:00:00Z","_id":"14461","month":"07","conference":{"start_date":"2023-07-23","name":"ICML: International Conference on Machine Learning","end_date":"2023-07-29","location":"Honolulu, Hawaii, HI, United States"},"external_id":{"arxiv":["2302.02390"]},"arxiv":1,"quality_controlled":"1","publication_status":"published","oa":1,"intvolume":" 202","publication":"Proceedings of the 40th International Conference on Machine Learning","acknowledged_ssus":[{"_id":"ScienComp"}],"alternative_title":["PMLR"],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2640-3498"]},"type":"conference"},{"page":"10072-10092","status":"public","project":[{"_id":"bd9ca328-d553-11ed-ba76-dc4f890cfe62","grant_number":"101019564","name":"The design and evaluation of modern fully dynamic data structures","call_identifier":"H2020"},{"name":"Wittgenstein Award - Monika Henzinger","_id":"34def286-11ca-11ed-8bc3-da5948e1613c","grant_number":"Z00422"},{"name":"Fast Algorithms for a Reactive Network Layer","grant_number":"P33775 ","_id":"bd9e3a2e-d553-11ed-ba76-8aa684ce17fe"}],"main_file_link":[{"url":"https://proceedings.mlr.press/v202/fichtenberger23a/fichtenberger23a.pdf","open_access":"1"}],"acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No.\r\n101019564 “The Design of Modern Fully Dynamic Data Structures (MoDynStruct)” and from the Austrian Science Fund (FWF) project Z 422-N, and project “Fast Algorithms for a Reactive Network Layer (ReactNet)”, P 33775-N, with additional funding from the netidee SCIENCE Stiftung, 2020–2024. 2020–2024. JU’s research was funded by Decanal Research Grant. A part of this work was done when JU was visiting Indian Statistical Institute, Delhi. The authors would like to thank Rajat Bhatia, Aleksandar Nikolov, Shanta Laisharam, Vern Paulsen, Ryan Rogers, Abhradeep Thakurta, and Sarvagya Upadhyay for useful discussions.","volume":202,"year":"2023","date_created":"2023-10-29T23:01:17Z","date_updated":"2025-07-15T12:51:52Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"ML Research Press","article_processing_charge":"No","title":"Constant matters: Fine-grained error bound on differentially private continual observation","abstract":[{"lang":"eng","text":"We study fine-grained error bounds for differentially private algorithms for counting under continual observation. Our main insight is that the matrix mechanism when using lower-triangular matrices can be used in the continual observation model. More specifically, we give an explicit factorization for the counting matrix Mcount and upper bound the error explicitly. We also give a fine-grained analysis, specifying the exact constant in the upper bound. Our analysis is based on upper and lower bounds of the completely bounded norm (cb-norm) of Mcount\r\n. Along the way, we improve the best-known bound of 28 years by Mathias (SIAM Journal on Matrix Analysis and Applications, 1993) on the cb-norm of Mcount for a large range of the dimension of Mcount. Furthermore, we are the first to give concrete error bounds for various problems under continual observation such as binary counting, maintaining a histogram, releasing an approximately cut-preserving synthetic graph, many graph-based statistics, and substring and episode counting. Finally, we note that our result can be used to get a fine-grained error bound for non-interactive local learning and the first lower bounds on the additive error for (ϵ,δ)-differentially-private counting under continual observation. Subsequent to this work, Henzinger et al. (SODA, 2023) showed that our factorization also achieves fine-grained mean-squared error."}],"day":"30","citation":{"ieee":"H. Fichtenberger, M. H. Henzinger, and J. Upadhyay, “Constant matters: Fine-grained error bound on differentially private continual observation,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10072–10092.","mla":"Fichtenberger, Hendrik, et al. “Constant Matters: Fine-Grained Error Bound on Differentially Private Continual Observation.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10072–92.","ista":"Fichtenberger H, Henzinger MH, Upadhyay J. 2023. Constant matters: Fine-grained error bound on differentially private continual observation. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 10072–10092.","apa":"Fichtenberger, H., Henzinger, M. H., & Upadhyay, J. (2023). Constant matters: Fine-grained error bound on differentially private continual observation. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10072–10092). Honolulu, Hawaii, HI, United States: ML Research Press.","ama":"Fichtenberger H, Henzinger MH, Upadhyay J. Constant matters: Fine-grained error bound on differentially private continual observation. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10072-10092.","chicago":"Fichtenberger, Hendrik, Monika H Henzinger, and Jalaj Upadhyay. “Constant Matters: Fine-Grained Error Bound on Differentially Private Continual Observation.” In Proceedings of the 40th International Conference on Machine Learning, 202:10072–92. ML Research Press, 2023.","short":"H. Fichtenberger, M.H. Henzinger, J. Upadhyay, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10072–10092."},"scopus_import":"1","author":[{"full_name":"Fichtenberger, Hendrik","last_name":"Fichtenberger","first_name":"Hendrik"},{"orcid":"0000-0002-5008-6530","full_name":"Henzinger, Monika H","last_name":"Henzinger","first_name":"Monika H","id":"540c9bbd-f2de-11ec-812d-d04a5be85630"},{"first_name":"Jalaj","full_name":"Upadhyay, Jalaj","last_name":"Upadhyay"}],"oa_version":"Published Version","ec_funded":1,"department":[{"_id":"MoHe"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2640-3498"]},"type":"conference","alternative_title":["PMLR"],"publication_status":"published","quality_controlled":"1","publication":"Proceedings of the 40th International Conference on Machine Learning","intvolume":" 202","oa":1,"_id":"14462","date_published":"2023-07-30T00:00:00Z","conference":{"name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23","end_date":"2023-07-29","location":"Honolulu, Hawaii, HI, United States"},"month":"07"},{"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1111/mec.17160"}],"article_type":"original","status":"public","acknowledgement":"We would like to thank members of the Littorina team for their advice and feedback during this project. In particular, we thank Alan Le Moan, who inspired us to look at heterozygosity differences to identify inversions, and Katherine Hearn for helping with the PCA scripts. We thank Edinburgh Genomics for library preparation and sequencing. Sample collections, sequencing and data preparation were supported by the European Research Council (ERC-2015-AdG-693030- BARRIERS) and the Natural Environment Research Council (NE/P001610/1). The analysis was supported by the Swedish Research Council (vetenskaprådet; 2018-03695_VR) and the Portuguese Foundation for Science and Technology (Fundación para a Ciência e Tecnologia) through a research project (PTDC/BIA-EVL/1614/2021) and CEEC contract (2020.00275.CEECIND).","date_created":"2023-10-29T23:01:17Z","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-12-13T13:05:27Z","publisher":"Wiley","pmid":1,"title":"Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana)","article_processing_charge":"Yes (in subscription journal)","abstract":[{"text":"Inversions are thought to play a key role in adaptation and speciation, suppressing recombination between diverging populations. Genes influencing adaptive traits cluster in inversions, and changes in inversion frequencies are associated with environmental differences. However, in many organisms, it is unclear if inversions are geographically and taxonomically widespread. The intertidal snail, Littorina saxatilis, is one such example. Strong associations between putative polymorphic inversions and phenotypic differences have been demonstrated between two ecotypes of L. saxatilis in Sweden and inferred elsewhere, but no direct evidence for inversion polymorphism currently exists across the species range. Using whole genome data from 107 snails, most inversion polymorphisms were found to be widespread across the species range. The frequencies of some inversion arrangements were significantly different among ecotypes, suggesting a parallel adaptive role. Many inversions were also polymorphic in the sister species, L. arcana, hinting at an ancient origin.","lang":"eng"}],"day":"16","isi":1,"citation":{"short":"J. Reeve, R.K. Butlin, E.L. Koch, S. Stankowski, R. Faria, Molecular Ecology (2023).","chicago":"Reeve, James, Roger K. Butlin, Eva L. Koch, Sean Stankowski, and Rui Faria. “Chromosomal Inversion Polymorphisms Are Widespread across the Species Ranges of Rough Periwinkles (Littorina Saxatilis and L. Arcana).” Molecular Ecology. Wiley, 2023. https://doi.org/10.1111/mec.17160.","apa":"Reeve, J., Butlin, R. K., Koch, E. L., Stankowski, S., & Faria, R. (2023). Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana). Molecular Ecology. Wiley. https://doi.org/10.1111/mec.17160","ama":"Reeve J, Butlin RK, Koch EL, Stankowski S, Faria R. Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana). Molecular Ecology. 2023. doi:10.1111/mec.17160","ista":"Reeve J, Butlin RK, Koch EL, Stankowski S, Faria R. 2023. Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana). Molecular Ecology.","mla":"Reeve, James, et al. “Chromosomal Inversion Polymorphisms Are Widespread across the Species Ranges of Rough Periwinkles (Littorina Saxatilis and L. Arcana).” Molecular Ecology, Wiley, 2023, doi:10.1111/mec.17160.","ieee":"J. Reeve, R. K. Butlin, E. L. Koch, S. Stankowski, and R. Faria, “Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana),” Molecular Ecology. Wiley, 2023."},"scopus_import":"1","oa_version":"Published Version","author":[{"full_name":"Reeve, James","last_name":"Reeve","first_name":"James"},{"full_name":"Butlin, Roger K.","last_name":"Butlin","first_name":"Roger K."},{"last_name":"Koch","full_name":"Koch, Eva L.","first_name":"Eva L."},{"last_name":"Stankowski","full_name":"Stankowski, Sean","id":"43161670-5719-11EA-8025-FABC3DDC885E","first_name":"Sean"},{"full_name":"Faria, Rui","last_name":"Faria","first_name":"Rui"}],"department":[{"_id":"NiBa"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["0962-1083"],"eissn":["1365-294X"]},"type":"journal_article","quality_controlled":"1","publication_status":"epub_ahead","oa":1,"publication":"Molecular Ecology","date_published":"2023-10-16T00:00:00Z","doi":"10.1111/mec.17160","_id":"14463","month":"10","external_id":{"isi":["001085119000001"],"pmid":["37843465"]}},{"oa_version":"Preprint","author":[{"first_name":"Áron","last_name":"Ambrus","full_name":"Ambrus, Áron"},{"first_name":"Mónika","last_name":"Csikós","full_name":"Csikós, Mónika"},{"last_name":"Kiss","full_name":"Kiss, Gergely","first_name":"Gergely"},{"last_name":"Pach","full_name":"Pach, János","id":"E62E3130-B088-11EA-B919-BF823C25FEA4","first_name":"János"},{"last_name":"Somlai","full_name":"Somlai, Gábor","first_name":"Gábor"}],"department":[{"_id":"HeEd"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["0129-0541"],"eissn":["1793-6373"]},"type":"journal_article","issue":"7","quality_controlled":"1","publication_status":"published","oa":1,"intvolume":" 34","publication":"International Journal of Foundations of Computer Science","doi":"10.1142/S012905412342008X","date_published":"2023-10-05T00:00:00Z","_id":"14464","month":"10","arxiv":1,"external_id":{"arxiv":["2205.11637"],"isi":["001080874400001"]},"page":"737-760","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2205.11637","open_access":"1"}],"article_type":"original","status":"public","volume":34,"date_created":"2023-10-29T23:01:18Z","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"World Scientific Publishing","date_updated":"2023-12-13T13:04:55Z","title":"Optimal embedded and enclosing isosceles triangles","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Given a triangle Δ, we study the problem of determining the smallest enclosing and largest embedded isosceles triangles of Δ with respect to area and perimeter. This problem was initially posed by Nandakumar [17, 22] and was first studied by Kiss, Pach, and Somlai [13], who showed that if Δ′ is the smallest area isosceles triangle containing Δ, then Δ′ and Δ share a side and an angle. In the present paper, we prove that for any triangle Δ, every maximum area isosceles triangle embedded in Δ and every maximum perimeter isosceles triangle embedded in Δ shares a side and an angle with Δ. Somewhat surprisingly, the case of minimum perimeter enclosing triangles is different: there are infinite families of triangles Δ whose minimum perimeter isosceles containers do not share a side and an angle with Δ."}],"day":"05","isi":1,"citation":{"apa":"Ambrus, Á., Csikós, M., Kiss, G., Pach, J., & Somlai, G. (2023). Optimal embedded and enclosing isosceles triangles. International Journal of Foundations of Computer Science. World Scientific Publishing. https://doi.org/10.1142/S012905412342008X","ama":"Ambrus Á, Csikós M, Kiss G, Pach J, Somlai G. Optimal embedded and enclosing isosceles triangles. International Journal of Foundations of Computer Science. 2023;34(7):737-760. doi:10.1142/S012905412342008X","ista":"Ambrus Á, Csikós M, Kiss G, Pach J, Somlai G. 2023. Optimal embedded and enclosing isosceles triangles. International Journal of Foundations of Computer Science. 34(7), 737–760.","chicago":"Ambrus, Áron, Mónika Csikós, Gergely Kiss, János Pach, and Gábor Somlai. “Optimal Embedded and Enclosing Isosceles Triangles.” International Journal of Foundations of Computer Science. World Scientific Publishing, 2023. https://doi.org/10.1142/S012905412342008X.","short":"Á. Ambrus, M. Csikós, G. Kiss, J. Pach, G. Somlai, International Journal of Foundations of Computer Science 34 (2023) 737–760.","ieee":"Á. Ambrus, M. Csikós, G. Kiss, J. Pach, and G. Somlai, “Optimal embedded and enclosing isosceles triangles,” International Journal of Foundations of Computer Science, vol. 34, no. 7. World Scientific Publishing, pp. 737–760, 2023.","mla":"Ambrus, Áron, et al. “Optimal Embedded and Enclosing Isosceles Triangles.” International Journal of Foundations of Computer Science, vol. 34, no. 7, World Scientific Publishing, 2023, pp. 737–60, doi:10.1142/S012905412342008X."},"scopus_import":"1"},{"department":[{"_id":"GradSch"},{"_id":"BjHo"}],"file":[{"success":1,"checksum":"17c64c1fb0d5f73252364bf98b0b9e1a","access_level":"open_access","content_type":"application/pdf","file_name":"2023_JourFluidMechanics_Marensi.pdf","date_updated":"2024-02-15T09:05:21Z","creator":"dernst","file_size":2804641,"date_created":"2024-02-15T09:05:21Z","relation":"main_file","file_id":"14996"}],"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"author":[{"full_name":"Marensi, Elena","orcid":"0000-0001-7173-4923","last_name":"Marensi","first_name":"Elena","id":"0BE7553A-1004-11EA-B805-18983DDC885E"},{"id":"66E74FA2-D8BF-11E9-8249-8DE2E5697425","first_name":"Gökhan","last_name":"Yalniz","full_name":"Yalniz, Gökhan","orcid":"0000-0002-8490-9312"},{"full_name":"Hof, Björn","orcid":"0000-0003-2057-2754","last_name":"Hof","first_name":"Björn","id":"3A374330-F248-11E8-B48F-1D18A9856A87"}],"oa_version":"Published Version","external_id":{"arxiv":["2212.12406"],"isi":["001088363700001"]},"arxiv":1,"month":"11","_id":"14466","doi":"10.1017/jfm.2023.780","date_published":"2023-11-10T00:00:00Z","oa":1,"publication":"Journal of Fluid Mechanics","intvolume":" 974","publication_status":"published","quality_controlled":"1","type":"journal_article","publication_identifier":{"issn":["0022-1120"],"eissn":["1469-7645"]},"file_date_updated":"2024-02-15T09:05:21Z","language":[{"iso":"eng"}],"keyword":["turbulence","transition to turbulence","patterns"],"article_processing_charge":"Yes (via OA deal)","title":"Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows","article_number":"A21","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Cambridge University Press","date_updated":"2024-02-15T09:06:23Z","ddc":["530"],"year":"2023","date_created":"2023-10-30T09:32:28Z","acknowledgement":"E.M. acknowledges funding from the ISTplus fellowship programme. G.Y. and B.H. acknowledge a grant from the Simons Foundation (662960, BH).","volume":974,"project":[{"_id":"238598C6-32DE-11EA-91FC-C7463DDC885E","grant_number":"662960","name":"Revisiting the Turbulence Problem Using Statistical Mechanics: Experimental Studies on Transitional and Turbulent Flows"}],"status":"public","article_type":"original","has_accepted_license":"1","citation":{"mla":"Marensi, Elena, et al. “Dynamics and Proliferation of Turbulent Stripes in Plane-Poiseuille and Plane-Couette Flows.” Journal of Fluid Mechanics, vol. 974, A21, Cambridge University Press, 2023, doi:10.1017/jfm.2023.780.","ieee":"E. Marensi, G. Yalniz, and B. Hof, “Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows,” Journal of Fluid Mechanics, vol. 974. Cambridge University Press, 2023.","short":"E. Marensi, G. Yalniz, B. Hof, Journal of Fluid Mechanics 974 (2023).","ama":"Marensi E, Yalniz G, Hof B. Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows. Journal of Fluid Mechanics. 2023;974. doi:10.1017/jfm.2023.780","apa":"Marensi, E., Yalniz, G., & Hof, B. (2023). Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows. Journal of Fluid Mechanics. Cambridge University Press. https://doi.org/10.1017/jfm.2023.780","chicago":"Marensi, Elena, Gökhan Yalniz, and Björn Hof. “Dynamics and Proliferation of Turbulent Stripes in Plane-Poiseuille and Plane-Couette Flows.” Journal of Fluid Mechanics. Cambridge University Press, 2023. https://doi.org/10.1017/jfm.2023.780.","ista":"Marensi E, Yalniz G, Hof B. 2023. Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows. Journal of Fluid Mechanics. 974, A21."},"day":"10","isi":1,"abstract":[{"text":"The first long-lived turbulent structures observable in planar shear flows take the form of localized stripes, inclined with respect to the mean flow direction. The dynamics of these stripes is central to transition, and recent studies proposed an analogy to directed percolation where the stripes’ proliferation is ultimately responsible for the turbulence becoming sustained. In the present study we focus on the internal stripe dynamics as well as on the eventual stripe expansion, and we compare the underlying mechanisms in pressure- and shear-driven planar flows, respectively, plane-Poiseuille and plane-Couette flow. Despite the similarities of the overall laminar–turbulence patterns, the stripe proliferation processes in the two cases are fundamentally different. Starting from the growth and sustenance of individual stripes, we find that in plane-Couette flow new streaks are created stochastically throughout the stripe whereas in plane-Poiseuille flow streak creation is deterministic and occurs locally at the downstream tip. Because of the up/downstream symmetry, Couette stripes, in contrast to Poiseuille stripes, have two weak and two strong laminar turbulent interfaces. These differences in symmetry as well as in internal growth give rise to two fundamentally different stripe splitting mechanisms. In plane-Poiseuille flow splitting is connected to the elongational growth of the original stripe, and it results from a break-off/shedding of the stripe's tail. In plane-Couette flow splitting follows from a broadening of the original stripe and a division along the stripe into two slimmer stripes.","lang":"eng"}]}]