[{"abstract":[{"lang":"eng","text":"Suppose we have two hash functions h1 and h2, but we trust the security of only one of them. To mitigate this worry, we wish to build a hash combiner Ch1,h2 which is secure so long as one of the underlying hash functions is. This question has been well-studied in the regime of collision resistance. In this case, concatenating the two hash function outputs clearly works. Unfortunately, a long series of works (Boneh and Boyen, CRYPTO’06; Pietrzak, Eurocrypt’07; Pietrzak, CRYPTO’08) showed no (noticeably) shorter combiner for collision resistance is possible.\r\nIn this work, we revisit this pessimistic state of affairs, motivated by the observation that collision-resistance is insufficient for many interesting applications of cryptographic hash functions anyway. We argue the right formulation of the “hash combiner” is to build what we call random oracle (RO) combiners, utilizing stronger assumptions for stronger constructions.\r\nIndeed, we circumvent the previous lower bounds for collision resistance by constructing a simple length-preserving RO combiner C˜h1,h2Z1,Z2(M)=h1(M,Z1)⊕h2(M,Z2),where Z1,Z2\r\n are random salts of appropriate length. We show that this extra randomness is necessary for RO combiners, and indeed our construction is somewhat tight with this lower bound.\r\nOn the negative side, we show that one cannot generically apply the composition theorem to further replace “monolithic” hash functions h1 and h2 by some simpler indifferentiable construction (such as the Merkle-Damgård transformation) from smaller components, such as fixed-length compression functions. Finally, despite this issue, we directly prove collision resistance of the Merkle-Damgård variant of our combiner, where h1 and h2 are replaced by iterative Merkle-Damgård hashes applied to a fixed-length compression function. Thus, we can still subvert the concatenation barrier for collision-resistance combiners while utilizing practically small fixed-length components underneath."}],"date_created":"2023-10-15T22:01:11Z","oa_version":"Preprint","publication":"43rd Annual International Cryptology Conference","title":"Random oracle combiners: Breaking the concatenation barrier for collision-resistance","department":[{"_id":"KrPi"}],"publisher":"Springer Nature","citation":{"apa":"Dodis, Y., Ferguson, N., Goldin, E., Hall, P., & Pietrzak, K. Z. (2023). Random oracle combiners: Breaking the concatenation barrier for collision-resistance. In 43rd Annual International Cryptology Conference (Vol. 14082, pp. 514–546). Santa Barbara, CA, United States: Springer Nature. https://doi.org/10.1007/978-3-031-38545-2_17","chicago":"Dodis, Yevgeniy, Niels Ferguson, Eli Goldin, Peter Hall, and Krzysztof Z Pietrzak. “Random Oracle Combiners: Breaking the Concatenation Barrier for Collision-Resistance.” In 43rd Annual International Cryptology Conference, 14082:514–46. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-38545-2_17.","ieee":"Y. Dodis, N. Ferguson, E. Goldin, P. Hall, and K. Z. Pietrzak, “Random oracle combiners: Breaking the concatenation barrier for collision-resistance,” in 43rd Annual International Cryptology Conference, Santa Barbara, CA, United States, 2023, vol. 14082, pp. 514–546.","short":"Y. Dodis, N. Ferguson, E. Goldin, P. Hall, K.Z. Pietrzak, in:, 43rd Annual International Cryptology Conference, Springer Nature, 2023, pp. 514–546.","mla":"Dodis, Yevgeniy, et al. “Random Oracle Combiners: Breaking the Concatenation Barrier for Collision-Resistance.” 43rd Annual International Cryptology Conference, vol. 14082, Springer Nature, 2023, pp. 514–46, doi:10.1007/978-3-031-38545-2_17.","ista":"Dodis Y, Ferguson N, Goldin E, Hall P, Pietrzak KZ. 2023. Random oracle combiners: Breaking the concatenation barrier for collision-resistance. 43rd Annual International Cryptology Conference. CRYPTO: Advances in Cryptology, LNCS, vol. 14082, 514–546.","ama":"Dodis Y, Ferguson N, Goldin E, Hall P, Pietrzak KZ. Random oracle combiners: Breaking the concatenation barrier for collision-resistance. In: 43rd Annual International Cryptology Conference. Vol 14082. Springer Nature; 2023:514-546. doi:10.1007/978-3-031-38545-2_17"},"publication_identifier":{"isbn":["9783031385445"],"issn":["0302-9743"],"eissn":["1611-3349"]},"status":"public","oa":1,"_id":"14428","year":"2023","volume":14082,"page":"514-546","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","scopus_import":"1","quality_controlled":"1","author":[{"first_name":"Yevgeniy","last_name":"Dodis","full_name":"Dodis, Yevgeniy"},{"full_name":"Ferguson, Niels","first_name":"Niels","last_name":"Ferguson"},{"full_name":"Goldin, Eli","last_name":"Goldin","first_name":"Eli"},{"full_name":"Hall, Peter","last_name":"Hall","first_name":"Peter"},{"last_name":"Pietrzak","orcid":"0000-0002-9139-1654","first_name":"Krzysztof Z","id":"3E04A7AA-F248-11E8-B48F-1D18A9856A87","full_name":"Pietrzak, Krzysztof Z"}],"date_published":"2023-08-09T00:00:00Z","article_processing_charge":"No","alternative_title":["LNCS"],"date_updated":"2023-10-16T08:02:11Z","doi":"10.1007/978-3-031-38545-2_17","conference":{"start_date":"2023-08-20","location":"Santa Barbara, CA, United States","end_date":"2023-08-24","name":"CRYPTO: Advances in Cryptology"},"month":"08","language":[{"iso":"eng"}],"day":"09","main_file_link":[{"url":"https://eprint.iacr.org/2023/1041","open_access":"1"}],"intvolume":" 14082","publication_status":"published"},{"day":"01","ddc":["510"],"language":[{"iso":"eng"}],"project":[{"call_identifier":"H2020","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","grant_number":"694227","name":"Analysis of quantum many-body systems"}],"month":"11","license":"https://creativecommons.org/licenses/by/4.0/","intvolume":" 404","publication_status":"published","file":[{"checksum":"1ae49b39247cb6b40ff75997381581b8","file_name":"2023_CommMathPhysics_Brooks.pdf","file_size":832375,"file_id":"14477","date_updated":"2023-10-31T12:21:39Z","date_created":"2023-10-31T12:21:39Z","success":1,"content_type":"application/pdf","creator":"dernst","access_level":"open_access","relation":"main_file"}],"date_published":"2023-11-01T00:00:00Z","author":[{"id":"B7ECF9FC-AA38-11E9-AC9A-0930E6697425","full_name":"Brooks, Morris","orcid":"0000-0002-6249-0928","last_name":"Brooks","first_name":"Morris"},{"id":"4AFD0470-F248-11E8-B48F-1D18A9856A87","full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521","last_name":"Seiringer","first_name":"Robert"}],"doi":"10.1007/s00220-023-04841-3","date_updated":"2023-10-31T12:22:51Z","article_processing_charge":"Yes (via OA deal)","scopus_import":"1","quality_controlled":"1","file_date_updated":"2023-10-31T12:21:39Z","tmp":{"image":"/images/cc_by.png","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"},"acknowledgement":"Funding from the European Union’s Horizon 2020 research and innovation programme under the ERC grant agreement No 694227 is acknowledged. Open access funding provided by Institute of Science and Technology (IST Austria).","status":"public","oa":1,"external_id":{"arxiv":["2207.03156"]},"article_type":"original","citation":{"ieee":"M. Brooks and R. Seiringer, “The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy,” Communications in Mathematical Physics, vol. 404. Springer Nature, pp. 287–337, 2023.","chicago":"Brooks, Morris, and Robert Seiringer. “The Fröhlich Polaron at Strong Coupling: Part I - The Quantum Correction to the Classical Energy.” Communications in Mathematical Physics. Springer Nature, 2023. https://doi.org/10.1007/s00220-023-04841-3.","apa":"Brooks, M., & Seiringer, R. (2023). The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. Springer Nature. https://doi.org/10.1007/s00220-023-04841-3","ama":"Brooks M, Seiringer R. The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. 2023;404:287-337. doi:10.1007/s00220-023-04841-3","short":"M. Brooks, R. Seiringer, Communications in Mathematical Physics 404 (2023) 287–337.","ista":"Brooks M, Seiringer R. 2023. The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. 404, 287–337.","mla":"Brooks, Morris, and Robert Seiringer. “The Fröhlich Polaron at Strong Coupling: Part I - The Quantum Correction to the Classical Energy.” Communications in Mathematical Physics, vol. 404, Springer Nature, 2023, pp. 287–337, doi:10.1007/s00220-023-04841-3."},"publication_identifier":{"issn":["0010-3616"],"eissn":["1432-0916"]},"page":"287-337","volume":404,"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14441","has_accepted_license":"1","year":"2023","arxiv":1,"abstract":[{"text":"We study the Fröhlich polaron model in R3, and establish the subleading term in the strong coupling asymptotics of its ground state energy, corresponding to the quantum corrections to the classical energy determined by the Pekar approximation.","lang":"eng"}],"department":[{"_id":"RoSe"}],"title":"The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy","publication":"Communications in Mathematical Physics","publisher":"Springer Nature","oa_version":"Published Version","ec_funded":1,"date_created":"2023-10-22T22:01:13Z"},{"intvolume":" 256","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2202.05088","open_access":"1"}],"publication_status":"published","day":"01","month":"09","language":[{"iso":"eng"}],"date_published":"2023-09-01T00:00:00Z","author":[{"last_name":"Kwan","orcid":"0000-0002-4003-7567","first_name":"Matthew Alan","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","full_name":"Kwan, Matthew Alan"},{"full_name":"Sah, Ashwin","first_name":"Ashwin","last_name":"Sah"},{"first_name":"Mehtaab","last_name":"Sawhney","full_name":"Sawhney, Mehtaab"},{"full_name":"Simkin, Michael","last_name":"Simkin","first_name":"Michael"}],"article_processing_charge":"Yes (in subscription journal)","doi":"10.1007/s11856-023-2513-9","date_updated":"2023-10-31T11:27:30Z","scopus_import":"1","quality_controlled":"1","volume":256,"page":"363-416","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","_id":"14444","year":"2023","oa":1,"acknowledgement":"Sah and Sawhney were supported by NSF Graduate Research Fellowship Program DGE-1745302. Sah was supported by the PD Soros Fellowship. Simkin was supported by the Center of Mathematical Sciences and Applications at Harvard University.","status":"public","issue":"2","external_id":{"arxiv":["2202.05088"]},"article_type":"original","citation":{"ama":"Kwan MA, Sah A, Sawhney M, Simkin M. Substructures in Latin squares. Israel Journal of Mathematics. 2023;256(2):363-416. doi:10.1007/s11856-023-2513-9","ista":"Kwan MA, Sah A, Sawhney M, Simkin M. 2023. Substructures in Latin squares. Israel Journal of Mathematics. 256(2), 363–416.","mla":"Kwan, Matthew Alan, et al. “Substructures in Latin Squares.” Israel Journal of Mathematics, vol. 256, no. 2, Springer Nature, 2023, pp. 363–416, doi:10.1007/s11856-023-2513-9.","short":"M.A. Kwan, A. Sah, M. Sawhney, M. Simkin, Israel Journal of Mathematics 256 (2023) 363–416.","chicago":"Kwan, Matthew Alan, Ashwin Sah, Mehtaab Sawhney, and Michael Simkin. “Substructures in Latin Squares.” Israel Journal of Mathematics. Springer Nature, 2023. https://doi.org/10.1007/s11856-023-2513-9.","ieee":"M. A. Kwan, A. Sah, M. Sawhney, and M. Simkin, “Substructures in Latin squares,” Israel Journal of Mathematics, vol. 256, no. 2. Springer Nature, pp. 363–416, 2023.","apa":"Kwan, M. A., Sah, A., Sawhney, M., & Simkin, M. (2023). Substructures in Latin squares. Israel Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s11856-023-2513-9"},"publication_identifier":{"eissn":["1565-8511"],"issn":["0021-2172"]},"publication":"Israel Journal of Mathematics","department":[{"_id":"MaKw"}],"title":"Substructures in Latin squares","publisher":"Springer Nature","date_created":"2023-10-22T22:01:14Z","oa_version":"Preprint","arxiv":1,"abstract":[{"lang":"eng","text":"We prove several results about substructures in Latin squares. First, we explain how to adapt our recent work on high-girth Steiner triple systems to the setting of Latin squares, resolving a conjecture of Linial that there exist Latin squares with arbitrarily high girth. As a consequence, we see that the number of order- n Latin squares with no intercalate (i.e., no 2×2 Latin subsquare) is at least (e−9/4n−o(n))n2. Equivalently, P[N=0]≥e−n2/4−o(n2)=e−(1+o(1))EN\r\n , where N is the number of intercalates in a uniformly random order- n Latin square. \r\nIn fact, extending recent work of Kwan, Sah, and Sawhney, we resolve the general large-deviation problem for intercalates in random Latin squares, up to constant factors in the exponent: for any constant 0<δ≤1 we have P[N≤(1−δ)EN]=exp(−Θ(n2)) and for any constant δ>0 we have P[N≥(1+δ)EN]=exp(−Θ(n4/3logn)). \r\nFinally, as an application of some new general tools for studying substructures in random Latin squares, we show that in almost all order- n Latin squares, the number of cuboctahedra (i.e., the number of pairs of possibly degenerate 2×2 submatrices with the same arrangement of symbols) is of order n4, which is the minimum possible. As observed by Gowers and Long, this number can be interpreted as measuring ``how associative'' the quasigroup associated with the Latin square is."}]},{"abstract":[{"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.","lang":"eng"}],"date_created":"2023-10-22T22:01:14Z","oa_version":"Published Version","publication":"Israel Journal of Mathematics","title":"Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes","department":[{"_id":"UlWa"}],"publisher":"Springer Nature","citation":{"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","ista":"Wagner U, Wild P. 2023. Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. 256(2), 675–717.","short":"U. Wagner, P. Wild, Israel Journal of Mathematics 256 (2023) 675–717.","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.","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.","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.","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"},"publication_identifier":{"eissn":["1565-8511"],"issn":["0021-2172"]},"oa":1,"status":"public","issue":"2","article_type":"original","external_id":{"isi":["001081646400010"]},"_id":"14445","year":"2023","has_accepted_license":"1","volume":256,"page":"675-717","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","scopus_import":"1","quality_controlled":"1","date_published":"2023-09-01T00:00:00Z","author":[{"full_name":"Wagner, Uli","id":"36690CA2-F248-11E8-B48F-1D18A9856A87","first_name":"Uli","last_name":"Wagner","orcid":"0000-0002-1494-0568"},{"full_name":"Wild, Pascal","id":"4C20D868-F248-11E8-B48F-1D18A9856A87","first_name":"Pascal","last_name":"Wild"}],"article_processing_charge":"Yes (via OA deal)","doi":"10.1007/s11856-023-2521-9","date_updated":"2023-12-13T13:09:07Z","tmp":{"image":"/images/cc_by.png","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"},"file_date_updated":"2023-10-31T11:20:31Z","isi":1,"month":"09","language":[{"iso":"eng"}],"ddc":["510"],"day":"01","intvolume":" 256","file":[{"file_size":623787,"checksum":"fbb05619fe4b650f341cc730425dd9c3","file_name":"2023_IsraelJourMath_Wagner.pdf","file_id":"14475","date_updated":"2023-10-31T11:20:31Z","content_type":"application/pdf","date_created":"2023-10-31T11:20:31Z","success":1,"relation":"main_file","access_level":"open_access","creator":"dernst"}],"publication_status":"published"},{"file_date_updated":"2023-10-31T12:07:23Z","tmp":{"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","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"author":[{"full_name":"Jakubík, Jozef","first_name":"Jozef","last_name":"Jakubík"},{"last_name":"Bui Thi Mai","first_name":"Phuong","id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","full_name":"Bui Thi Mai, Phuong"},{"first_name":"Martina","last_name":"Chvosteková","full_name":"Chvosteková, Martina"},{"full_name":"Krakovská, Anna","first_name":"Anna","last_name":"Krakovská"}],"date_published":"2023-08-01T00:00:00Z","doi":"10.2478/msr-2023-0023","date_updated":"2023-10-31T12:12:47Z","article_processing_charge":"Yes","scopus_import":"1","quality_controlled":"1","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","intvolume":" 23","publication_status":"published","file":[{"file_name":"2023_MeasurementScienceRev_Jakubik.pdf","checksum":"b069cc10fa6a7c96b2bc9f728165f9e6","file_size":2639783,"file_id":"14476","date_updated":"2023-10-31T12:07:23Z","success":1,"date_created":"2023-10-31T12:07:23Z","content_type":"application/pdf","creator":"dernst","access_level":"open_access","relation":"main_file"}],"day":"01","ddc":["510"],"language":[{"iso":"eng"}],"month":"08","title":"Against the flow of time with multi-output models","department":[{"_id":"ChLa"}],"publication":"Measurement Science Review","publisher":"Sciendo","oa_version":"Published Version","date_created":"2023-10-22T22:01:15Z","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."}],"page":"175-183","volume":23,"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14446","has_accepted_license":"1","year":"2023","status":"public","oa":1,"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.","article_type":"original","issue":"4","citation":{"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","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.","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.","short":"J. Jakubík, M. Phuong, M. Chvosteková, A. Krakovská, Measurement Science Review 23 (2023) 175–183.","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.","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.","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"},"publication_identifier":{"eissn":["1335-8871"]}},{"date_published":"2023-10-13T00:00:00Z","author":[{"first_name":"Kristýna","last_name":"Bieleszová","full_name":"Bieleszová, Kristýna"},{"last_name":"Hladík","first_name":"Pavel","full_name":"Hladík, Pavel"},{"last_name":"Kubala","first_name":"Martin","full_name":"Kubala, Martin"},{"full_name":"Napier, Richard","last_name":"Napier","first_name":"Richard"},{"full_name":"Brunoni, Federica","last_name":"Brunoni","first_name":"Federica"},{"orcid":"0000-0003-4783-1752","last_name":"Gelová","first_name":"Zuzana","id":"0AE74790-0E0B-11E9-ABC7-1ACFE5697425","full_name":"Gelová, Zuzana"},{"full_name":"Fiedler, Lukas","id":"7c417475-8972-11ed-ae7b-8b674ca26986","first_name":"Lukas","last_name":"Fiedler"},{"id":"57a1567c-8314-11eb-9063-c9ddc3451a54","full_name":"Kulich, Ivan","last_name":"Kulich","first_name":"Ivan"},{"full_name":"Strnad, Miroslav","first_name":"Miroslav","last_name":"Strnad"},{"full_name":"Doležal, Karel","first_name":"Karel","last_name":"Doležal"},{"first_name":"Ondřej","last_name":"Novák","full_name":"Novák, Ondřej"},{"full_name":"Friml, Jiří","id":"4159519E-F248-11E8-B48F-1D18A9856A87","first_name":"Jiří","last_name":"Friml","orcid":"0000-0002-8302-7596"},{"first_name":"Asta","last_name":"Žukauskaitė","full_name":"Žukauskaitė, Asta"}],"date_updated":"2023-12-13T13:08:25Z","doi":"10.1007/s10725-023-01083-0","article_processing_charge":"Yes (via OA deal)","scopus_import":"1","quality_controlled":"1","day":"13","language":[{"iso":"eng"}],"month":"10","isi":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s10725-023-01083-0"}],"publication_status":"epub_ahead","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."}],"title":"New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana","department":[{"_id":"JiFr"}],"publication":"Plant Growth Regulation","publisher":"Springer Nature","oa_version":"Published Version","date_created":"2023-10-22T22:01:15Z","oa":1,"status":"public","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.","external_id":{"isi":["001084334300001"]},"article_type":"original","citation":{"ieee":"K. Bieleszová et al., “New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana,” Plant Growth Regulation. Springer Nature, 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.","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","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","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.","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).","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."},"publication_identifier":{"eissn":["1573-5087"],"issn":["0167-6903"]},"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14447","year":"2023"},{"conference":{"end_date":"2023-06-24","name":"CVPR: Conference on Computer Vision and Pattern Recognition","start_date":"2023-06-17","location":"Vancouver, Canada"},"date_updated":"2023-10-31T12:01:24Z","doi":"10.1109/CVPR52729.2023.01153","article_processing_charge":"No","author":[{"full_name":"Kolmogorov, Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","first_name":"Vladimir","last_name":"Kolmogorov"}],"date_published":"2023-08-22T00:00:00Z","quality_controlled":"1","scopus_import":"1","publication_status":"published","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2010.09567","open_access":"1"}],"intvolume":" 2023","day":"22","language":[{"iso":"eng"}],"month":"08","publisher":"IEEE","department":[{"_id":"VlKo"}],"title":"Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions","publication":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","oa_version":"Preprint","date_created":"2023-10-22T22:01:16Z","arxiv":1,"abstract":[{"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.","lang":"eng"}],"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"11980-11989","volume":2023,"year":"2023","_id":"14448","external_id":{"arxiv":["2010.09567"]},"oa":1,"status":"public","publication_identifier":{"issn":["1063-6919"],"isbn":["9798350301298"]},"citation":{"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","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.","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.","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.","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"}},{"abstract":[{"lang":"eng","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."}],"publication":"Frontiers in Microbiology","department":[{"_id":"ScienComp"}],"title":"Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action","publisher":"Frontiers","date_created":"2023-10-22T22:01:16Z","oa_version":"Published Version","oa":1,"status":"public","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.","external_id":{"isi":["001080536000001"],"pmid":["37808321"]},"article_type":"original","citation":{"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","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.","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).","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.","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.","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.","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"},"publication_identifier":{"eissn":["1664-302X"]},"volume":14,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","_id":"14449","year":"2023","has_accepted_license":"1","author":[{"last_name":"D’Elia","first_name":"Domenica","full_name":"D’Elia, Domenica"},{"first_name":"Jaak","last_name":"Truu","full_name":"Truu, Jaak"},{"full_name":"Lahti, Leo","first_name":"Leo","last_name":"Lahti"},{"first_name":"Magali","last_name":"Berland","full_name":"Berland, Magali"},{"first_name":"Georgios","last_name":"Papoutsoglou","full_name":"Papoutsoglou, Georgios"},{"full_name":"Ceci, Michelangelo","first_name":"Michelangelo","last_name":"Ceci"},{"full_name":"Zomer, Aldert","last_name":"Zomer","first_name":"Aldert"},{"first_name":"Marta B.","last_name":"Lopes","full_name":"Lopes, Marta B."},{"full_name":"Ibrahimi, Eliana","first_name":"Eliana","last_name":"Ibrahimi"},{"first_name":"Aleksandra","last_name":"Gruca","full_name":"Gruca, Aleksandra"},{"first_name":"Alina","last_name":"Nechyporenko","full_name":"Nechyporenko, Alina"},{"last_name":"Frohme","first_name":"Marcus","full_name":"Frohme, Marcus"},{"full_name":"Klammsteiner, Thomas","last_name":"Klammsteiner","first_name":"Thomas"},{"full_name":"Pau, Enrique Carrillo De Santa","first_name":"Enrique Carrillo De Santa","last_name":"Pau"},{"full_name":"Marcos-Zambrano, Laura Judith","first_name":"Laura Judith","last_name":"Marcos-Zambrano"},{"last_name":"Hron","first_name":"Karel","full_name":"Hron, Karel"},{"last_name":"Pio","first_name":"Gianvito","full_name":"Pio, Gianvito"},{"last_name":"Simeon","first_name":"Andrea","full_name":"Simeon, Andrea"},{"last_name":"Suharoschi","first_name":"Ramona","full_name":"Suharoschi, Ramona"},{"last_name":"Moreno-Indias","first_name":"Isabel","full_name":"Moreno-Indias, Isabel"},{"full_name":"Temko, Andriy","first_name":"Andriy","last_name":"Temko"},{"first_name":"Miroslava","last_name":"Nedyalkova","full_name":"Nedyalkova, Miroslava"},{"full_name":"Apostol, Elena Simona","last_name":"Apostol","first_name":"Elena Simona"},{"full_name":"Truică, Ciprian Octavian","last_name":"Truică","first_name":"Ciprian Octavian"},{"full_name":"Shigdel, Rajesh","first_name":"Rajesh","last_name":"Shigdel"},{"full_name":"Telalović, Jasminka Hasić","last_name":"Telalović","first_name":"Jasminka Hasić"},{"first_name":"Erik","last_name":"Bongcam-Rudloff","full_name":"Bongcam-Rudloff, Erik"},{"full_name":"Przymus, Piotr","first_name":"Piotr","last_name":"Przymus"},{"full_name":"Jordamović, Naida Babić","last_name":"Jordamović","first_name":"Naida Babić"},{"full_name":"Falquet, Laurent","first_name":"Laurent","last_name":"Falquet"},{"full_name":"Tarazona, Sonia","last_name":"Tarazona","first_name":"Sonia"},{"first_name":"Alexia","last_name":"Sampri","full_name":"Sampri, Alexia"},{"full_name":"Isola, Gaetano","last_name":"Isola","first_name":"Gaetano"},{"last_name":"Pérez-Serrano","first_name":"David","full_name":"Pérez-Serrano, David"},{"first_name":"Vladimir","last_name":"Trajkovik","full_name":"Trajkovik, Vladimir"},{"last_name":"Klucar","first_name":"Lubos","full_name":"Klucar, Lubos"},{"first_name":"Tatjana","last_name":"Loncar-Turukalo","full_name":"Loncar-Turukalo, Tatjana"},{"first_name":"Aki S.","last_name":"Havulinna","full_name":"Havulinna, Aki S."},{"full_name":"Jansen, Christian","id":"837b2259-bcc9-11ed-a196-ae55927bc6e2","first_name":"Christian","last_name":"Jansen"},{"full_name":"Bertelsen, Randi J.","last_name":"Bertelsen","first_name":"Randi J."},{"last_name":"Claesson","first_name":"Marcus Joakim","full_name":"Claesson, Marcus Joakim"}],"date_published":"2023-09-25T00:00:00Z","article_processing_charge":"Yes","date_updated":"2023-12-13T13:07:21Z","doi":"10.3389/fmicb.2023.1257002","scopus_import":"1","quality_controlled":"1","file_date_updated":"2023-10-30T13:38:48Z","article_number":"1257002","tmp":{"image":"/images/cc_by.png","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"},"pmid":1,"ddc":["000"],"day":"25","month":"09","isi":1,"language":[{"iso":"eng"}],"intvolume":" 14","file":[{"relation":"main_file","creator":"dernst","access_level":"open_access","content_type":"application/pdf","date_created":"2023-10-30T13:38:48Z","success":1,"file_id":"14471","date_updated":"2023-10-30T13:38:48Z","file_size":505078,"checksum":"6c0acdd8fa111a699826957b8dff19d5","file_name":"2023_FrontiersMicrobiology_DElia.pdf"}],"publication_status":"published"},{"publication_status":"epub_ahead","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s00521-023-09033-7"}],"month":"10","language":[{"iso":"eng"}],"project":[{"_id":"fc31cba2-9c52-11eb-aca3-ff467d239cd2","name":"Taming Complexity in Partial Differential Systems","grant_number":"F6504"},{"call_identifier":"H2020","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"day":"05","quality_controlled":"1","scopus_import":"1","article_processing_charge":"Yes (via OA deal)","doi":"10.1007/s00521-023-09033-7","date_updated":"2023-10-31T10:58:28Z","date_published":"2023-10-05T00:00:00Z","author":[{"first_name":"Federico","last_name":"Cornalba","orcid":"0000-0002-6269-5149","full_name":"Cornalba, Federico","id":"2CEB641C-A400-11E9-A717-D712E6697425"},{"full_name":"Disselkamp, Constantin","first_name":"Constantin","last_name":"Disselkamp"},{"first_name":"Davide","last_name":"Scassola","full_name":"Scassola, Davide"},{"last_name":"Helf","first_name":"Christopher","full_name":"Helf, Christopher"}],"year":"2023","_id":"14451","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","publication_identifier":{"eissn":["1433-3058"],"issn":["0941-0643"]},"citation":{"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.","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","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.","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."},"external_id":{"arxiv":["2203.04579"]},"article_type":"original","status":"public","oa":1,"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","ec_funded":1,"oa_version":"Published Version","publisher":"Springer Nature","publication":"Neural Computing and Applications","title":"Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading","department":[{"_id":"JuFi"}],"abstract":[{"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.","lang":"eng"}],"arxiv":1},{"publication_status":"published","file":[{"file_name":"2023_Genetics_Barton.pdf","checksum":"3f65b1fbe813e2f4dbb5d2b5e891844a","file_size":1439032,"date_updated":"2023-10-30T12:57:53Z","file_id":"14469","success":1,"date_created":"2023-10-30T12:57:53Z","content_type":"application/pdf","creator":"dernst","access_level":"open_access","relation":"main_file"}],"intvolume":" 225","day":"01","ddc":["570"],"project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"},{"_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00","grant_number":"101055327","name":"Understanding the evolution of continuous genomes"}],"language":[{"iso":"eng"}],"month":"10","article_number":"iyad133","file_date_updated":"2023-10-30T12:57:53Z","tmp":{"image":"/images/cc_by.png","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"},"doi":"10.1093/genetics/iyad133","related_material":{"record":[{"id":"12949","status":"public","relation":"research_data"}]},"date_updated":"2025-05-28T11:42:48Z","article_processing_charge":"Yes (in subscription journal)","date_published":"2023-10-01T00:00:00Z","author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H"},{"first_name":"Alison M.","last_name":"Etheridge","full_name":"Etheridge, Alison M."},{"full_name":"Véber, Amandine","last_name":"Véber","first_name":"Amandine"}],"quality_controlled":"1","scopus_import":"1","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":225,"has_accepted_license":"1","year":"2023","_id":"14452","article_type":"original","external_id":{"arxiv":["2211.03515"]},"issue":"2","oa":1,"status":"public","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.","publication_identifier":{"eissn":["1943-2631"],"issn":["0016-6731"]},"citation":{"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.","ieee":"N. H. Barton, A. M. Etheridge, and A. Véber, “The infinitesimal model with dominance,” Genetics, vol. 225, no. 2. Oxford Academic, 2023.","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","ama":"Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics. 2023;225(2). doi:10.1093/genetics/iyad133","short":"N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).","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.","ista":"Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance. Genetics. 225(2), iyad133."},"publisher":"Oxford Academic","department":[{"_id":"NiBa"}],"title":"The infinitesimal model with dominance","publication":"Genetics","oa_version":"Published Version","date_created":"2023-10-29T23:01:15Z","ec_funded":1,"arxiv":1,"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."}]},{"isi":1,"month":"10","project":[{"_id":"629205d8-2b32-11ec-9570-e1356ff73576","name":"organization of CLoUdS, and implications of Tropical cyclones and for the Energetics of the tropics, in current and waRming climate","grant_number":"805041","call_identifier":"H2020"}],"language":[{"iso":"eng"}],"ddc":["550"],"day":"01","file":[{"relation":"main_file","access_level":"open_access","creator":"dernst","content_type":"application/pdf","date_created":"2023-10-30T13:31:42Z","success":1,"date_updated":"2023-10-30T13:31:42Z","file_id":"14470","file_size":1975210,"checksum":"43e6a1a35b663843c7d3f8d0caaca1a5","file_name":"2023_JAMES_Abramian.pdf"}],"publication_status":"published","intvolume":" 15","quality_controlled":"1","scopus_import":"1","article_processing_charge":"Yes","doi":"10.1029/2022MS003477","date_updated":"2023-12-13T13:06:40Z","date_published":"2023-10-01T00:00:00Z","author":[{"last_name":"Abramian","first_name":"Sophie","full_name":"Abramian, Sophie"},{"full_name":"Muller, Caroline J","id":"f978ccb0-3f7f-11eb-b193-b0e2bd13182b","first_name":"Caroline J","last_name":"Muller","orcid":"0000-0001-5836-5350"},{"last_name":"Risi","first_name":"Camille","full_name":"Risi, Camille"}],"tmp":{"image":"/images/cc_by.png","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"},"article_number":"e2022MS003477","file_date_updated":"2023-10-30T13:31:42Z","publication_identifier":{"eissn":["1942-2466"]},"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.","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.","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","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","short":"S. Abramian, C.J. Muller, C. Risi, Journal of Advances in Modeling Earth Systems 15 (2023).","ista":"Abramian S, Muller CJ, Risi C. 2023. Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. 15(10), e2022MS003477.","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."},"issue":"10","external_id":{"isi":["001084933600001"]},"article_type":"original","status":"public","oa":1,"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.","year":"2023","has_accepted_license":"1","_id":"14453","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","volume":15,"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"}],"ec_funded":1,"date_created":"2023-10-29T23:01:15Z","oa_version":"Published Version","publisher":"Wiley","publication":"Journal of Advances in Modeling Earth Systems","title":"Extreme precipitation in tropical squall lines","department":[{"_id":"CaMu"}]},{"ec_funded":1,"date_created":"2023-10-29T23:01:15Z","oa_version":"Preprint","publisher":"Springer Nature","publication":"23rd International Conference on Runtime Verification","department":[{"_id":"ToHe"}],"title":"Monitoring algorithmic fairness under partial observations","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."}],"arxiv":1,"year":"2023","_id":"14454","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","volume":14245,"page":"291-311","publication_identifier":{"isbn":["9783031442667"],"issn":["0302-9743"],"eissn":["1611-3349"]},"citation":{"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","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.","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.","short":"T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference on Runtime Verification, Springer Nature, 2023, pp. 291–311.","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.","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.","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"},"external_id":{"arxiv":["2308.00341"]},"status":"public","acknowledgement":"This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.","oa":1,"conference":{"name":"RV: Conference on Runtime Verification","end_date":"2023-10-06","location":"Thessaloniki, Greece","start_date":"2023-10-03"},"quality_controlled":"1","scopus_import":"1","article_processing_charge":"No","date_updated":"2023-10-31T11:48:20Z","doi":"10.1007/978-3-031-44267-4_15","alternative_title":["LNCS"],"author":[{"first_name":"Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger","full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Konstantin","orcid":"0000-0001-8974-2542","last_name":"Kueffner","full_name":"Kueffner, Konstantin","id":"8121a2d0-dc85-11ea-9058-af578f3b4515"},{"last_name":"Mallik","orcid":"0000-0001-9864-7475","first_name":"Kaushik","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","full_name":"Mallik, Kaushik"}],"date_published":"2023-10-01T00:00:00Z","publication_status":"published","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2308.00341","open_access":"1"}],"intvolume":" 14245","month":"10","language":[{"iso":"eng"}],"project":[{"grant_number":"101020093","name":"Vigilant Algorithmic Monitoring of Software","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020"}],"day":"01"},{"month":"10","isi":1,"language":[{"iso":"eng"}],"pmid":1,"ddc":["570"],"day":"03","intvolume":" 14","file":[{"date_updated":"2023-10-30T12:48:40Z","file_id":"14468","file_size":147878,"file_name":"2023_FrontiersPsychiatry_Narzisi.pdf","checksum":"0a76373e9a4c0fc199f80380de257e86","relation":"main_file","creator":"dernst","access_level":"open_access","content_type":"application/pdf","success":1,"date_created":"2023-10-30T12:48:40Z"}],"publication_status":"published","scopus_import":"1","quality_controlled":"1","date_published":"2023-10-03T00:00:00Z","author":[{"first_name":"Antonio","last_name":"Narzisi","full_name":"Narzisi, Antonio"},{"full_name":"Halladay, Alycia","first_name":"Alycia","last_name":"Halladay"},{"full_name":"Masi, Gabriele","last_name":"Masi","first_name":"Gabriele"},{"full_name":"Novarino, Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","first_name":"Gaia","orcid":"0000-0002-7673-7178","last_name":"Novarino"},{"last_name":"Lord","first_name":"Catherine","full_name":"Lord, Catherine"}],"article_processing_charge":"Yes","doi":"10.3389/fpsyt.2023.1287879","date_updated":"2023-12-13T13:06:07Z","tmp":{"image":"/images/cc_by.png","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"},"file_date_updated":"2023-10-30T12:48:40Z","article_number":"1287879","citation":{"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.","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.","short":"A. Narzisi, A. Halladay, G. Masi, G. Novarino, C. Lord, Frontiers in Psychiatry 14 (2023).","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","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","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.","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."},"publication_identifier":{"eissn":["1664-0640"]},"oa":1,"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.","status":"public","external_id":{"pmid":["37854442"],"isi":["001084841700001"]},"article_type":"letter_note","_id":"14455","has_accepted_license":"1","year":"2023","volume":14,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","date_created":"2023-10-29T23:01:16Z","oa_version":"Published Version","publication":"Frontiers in Psychiatry","department":[{"_id":"GaNo"}],"title":"Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment","publisher":"Frontiers"},{"volume":14292,"page":"333-347","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","_id":"14456","year":"2023","oa":1,"status":"public","external_id":{"arxiv":["2307.10847"]},"citation":{"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.","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.","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","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.","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.","short":"J.M. Křišťan, J. Svoboda, in:, 24th International Symposium on Fundamentals of Computation Theory, Springer Nature, 2023, pp. 333–347."},"publication_identifier":{"isbn":["9783031435867"],"issn":["0302-9743"],"eissn":["1611-3349"]},"publication":"24th International Symposium on Fundamentals of Computation Theory","title":"Shortest dominating set reconfiguration under token sliding","department":[{"_id":"KrCh"}],"publisher":"Springer Nature","date_created":"2023-10-29T23:01:16Z","oa_version":"Preprint","arxiv":1,"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"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2307.10847"}],"intvolume":" 14292","publication_status":"published","day":"21","month":"09","language":[{"iso":"eng"}],"conference":{"start_date":"2023-09-18","location":"Trier, Germany","end_date":"2023-09-21","name":"FCT: Fundamentals of Computation Theory"},"author":[{"full_name":"Křišťan, Jan Matyáš","first_name":"Jan Matyáš","last_name":"Křišťan"},{"first_name":"Jakub","orcid":"0000-0002-1419-3267","last_name":"Svoboda","full_name":"Svoboda, Jakub","id":"130759D2-D7DD-11E9-87D2-DE0DE6697425"}],"date_published":"2023-09-21T00:00:00Z","article_processing_charge":"No","date_updated":"2024-01-22T08:10:49Z","alternative_title":["LNCS"],"doi":"10.1007/978-3-031-43587-4_24","related_material":{"link":[{"url":"https://doi.org/10.1007/978-3-031-43587-4_31","relation":"erratum"}]},"scopus_import":"1","quality_controlled":"1"},{"date_updated":"2023-10-31T11:43:12Z","doi":"10.1007/978-3-031-44469-2_11","alternative_title":["LNCS"],"article_processing_charge":"No","author":[{"full_name":"Hoffmann, Charlotte","id":"0f78d746-dc7d-11ea-9b2f-83f92091afe7","first_name":"Charlotte","orcid":"0000-0003-2027-5549","last_name":"Hoffmann"},{"first_name":"Mark","last_name":"Simkin","full_name":"Simkin, Mark"}],"date_published":"2023-10-01T00:00:00Z","quality_controlled":"1","scopus_import":"1","conference":{"name":"LATINCRYPT: Conference on Cryptology and Information Security in Latin America","end_date":"2023-10-06","location":"Quito, Ecuador","start_date":"2023-10-03"},"day":"01","language":[{"iso":"eng"}],"month":"10","publication_status":"published","intvolume":" 14168","main_file_link":[{"url":"https://eprint.iacr.org/2023/1017","open_access":"1"}],"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"}],"publisher":"Springer Nature","department":[{"_id":"KrPi"}],"title":"Stronger lower bounds for leakage-resilient secret sharing","publication":"8th International Conference on Cryptology and Information Security in Latin America","oa_version":"Preprint","date_created":"2023-10-29T23:01:16Z","oa":1,"status":"public","publication_identifier":{"isbn":["9783031444685"],"eissn":["1611-3349"],"issn":["0302-9743"]},"citation":{"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","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.","short":"C. Hoffmann, M. Simkin, in:, 8th International Conference on Cryptology and Information Security in Latin America, Springer Nature, 2023, 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.","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.","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.","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"},"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"215-228","volume":14168,"year":"2023","_id":"14457"},{"oa_version":"Preprint","date_created":"2023-10-29T23:01:16Z","ec_funded":1,"department":[{"_id":"DaAl"}],"title":"SparseGPT: Massive language models can be accurately pruned in one-shot","publication":"Proceedings of the 40th International Conference on Machine Learning","publisher":"ML Research Press","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"}],"arxiv":1,"_id":"14458","year":"2023","page":"10323-10337","volume":202,"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"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.","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.","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.","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.","short":"E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, 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.","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."},"publication_identifier":{"eissn":["2640-3498"]},"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.","oa":1,"status":"public","external_id":{"arxiv":["2301.00774"]},"conference":{"start_date":"2023-07-23","location":"Honolulu, Hawaii, HI, United States","end_date":"2023-07-29","name":"ICML: International Conference on Machine Learning"},"acknowledged_ssus":[{"_id":"ScienComp"}],"scopus_import":"1","quality_controlled":"1","author":[{"first_name":"Elias","last_name":"Frantar","full_name":"Frantar, Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f"},{"first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"date_published":"2023-07-30T00:00:00Z","alternative_title":["PMLR"],"date_updated":"2023-10-31T09:59:42Z","article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2301.00774","open_access":"1"}],"intvolume":" 202","publication_status":"published","language":[{"iso":"eng"}],"project":[{"call_identifier":"H2020","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"month":"07","day":"30"},{"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2212.13468"}],"intvolume":" 202","publication_status":"published","day":"30","month":"07","language":[{"iso":"eng"}],"project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"conference":{"name":"ICML: International Conference on Machine Learning","end_date":"2023-07-29","location":"Honolulu, Hawaii, HI, United States","start_date":"2023-07-23"},"date_published":"2023-07-30T00:00:00Z","author":[{"id":"F2B06EC2-C99E-11E9-89F0-752EE6697425","full_name":"Shevchenko, Aleksandr","last_name":"Shevchenko","first_name":"Aleksandr"},{"id":"94ec913c-dc85-11ea-9058-e5051ab2428b","full_name":"Kögler, Kevin","last_name":"Kögler","first_name":"Kevin"},{"full_name":"Hassani, Hamed","last_name":"Hassani","first_name":"Hamed"},{"last_name":"Mondelli","orcid":"0000-0002-3242-7020","first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco"}],"article_processing_charge":"No","alternative_title":["PMLR"],"date_updated":"2024-09-10T13:03:19Z","scopus_import":"1","quality_controlled":"1","volume":202,"page":"31151-31209","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","_id":"14459","year":"2023","status":"public","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).","oa":1,"external_id":{"arxiv":["2212.13468"]},"citation":{"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.","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.","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.","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.","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.","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."},"publication_identifier":{"eissn":["2640-3498"]},"publication":"Proceedings of the 40th International Conference on Machine Learning","title":"Fundamental limits of two-layer autoencoders, and achieving them with gradient methods","department":[{"_id":"MaMo"},{"_id":"DaAl"}],"publisher":"ML Research Press","date_created":"2023-10-29T23:01:17Z","oa_version":"Preprint","arxiv":1,"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"}]},{"conference":{"location":"Honolulu, Hawaii, HI, United States","start_date":"2023-07-23","name":"ICML: International Conference on Machine Learning","end_date":"2023-07-29"},"scopus_import":"1","quality_controlled":"1","date_published":"2023-07-30T00:00:00Z","author":[{"id":"66374281-f394-11eb-9cf6-869147deecc0","full_name":"Nikdan, Mahdi","last_name":"Nikdan","first_name":"Mahdi"},{"last_name":"Pegolotti","first_name":"Tommaso","full_name":"Pegolotti, Tommaso"},{"id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","full_name":"Iofinova, Eugenia B","last_name":"Iofinova","orcid":"0000-0002-7778-3221","first_name":"Eugenia B"},{"first_name":"Eldar","last_name":"Kurtic","full_name":"Kurtic, Eldar","id":"47beb3a5-07b5-11eb-9b87-b108ec578218"},{"first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","alternative_title":["PMLR"],"date_updated":"2023-10-31T09:33:51Z","intvolume":" 202","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2302.04852","open_access":"1"}],"publication_status":"published","month":"07","language":[{"iso":"eng"}],"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","call_identifier":"H2020"}],"day":"30","date_created":"2023-10-29T23:01:17Z","ec_funded":1,"oa_version":"Preprint","publication":"Proceedings of the 40th International Conference on Machine Learning","department":[{"_id":"DaAl"}],"title":"SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge","publisher":"ML Research Press","abstract":[{"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.","lang":"eng"}],"arxiv":1,"_id":"14460","year":"2023","volume":202,"page":"26215-26227","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","citation":{"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.","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.","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.","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.","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.","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.","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."},"publication_identifier":{"eissn":["2640-3498"]},"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. ","status":"public","oa":1,"external_id":{"arxiv":["2302.04852"]}},{"volume":202,"page":"24020-24044","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","_id":"14461","year":"2023","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).","status":"public","oa":1,"external_id":{"arxiv":["2302.02390"]},"citation":{"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.","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.","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.","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.","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.","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.","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."},"publication_identifier":{"eissn":["2640-3498"]},"publication":"Proceedings of the 40th International Conference on Machine Learning","title":"Quantized distributed training of large models with convergence guarantees","department":[{"_id":"DaAl"}],"publisher":"ML Research Press","date_created":"2023-10-29T23:01:17Z","ec_funded":1,"oa_version":"Preprint","arxiv":1,"abstract":[{"lang":"eng","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."}],"intvolume":" 202","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2302.02390"}],"publication_status":"published","day":"30","month":"07","project":[{"call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning"}],"language":[{"iso":"eng"}],"conference":{"start_date":"2023-07-23","location":"Honolulu, Hawaii, HI, United States","end_date":"2023-07-29","name":"ICML: International Conference on Machine Learning"},"acknowledged_ssus":[{"_id":"ScienComp"}],"date_published":"2023-07-30T00:00:00Z","author":[{"first_name":"Ilia","last_name":"Markov","full_name":"Markov, Ilia","id":"D0CF4148-C985-11E9-8066-0BDEE5697425"},{"full_name":"Vladu, Adrian","last_name":"Vladu","first_name":"Adrian"},{"first_name":"Qi","last_name":"Guo","full_name":"Guo, Qi"},{"first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","date_updated":"2023-10-31T09:40:45Z","alternative_title":["PMLR"],"scopus_import":"1","quality_controlled":"1"},{"intvolume":" 202","main_file_link":[{"url":"https://proceedings.mlr.press/v202/fichtenberger23a/fichtenberger23a.pdf","open_access":"1"}],"publication_status":"published","day":"30","month":"07","language":[{"iso":"eng"}],"project":[{"name":"The design and evaluation of modern fully dynamic data structures","grant_number":"101019564","_id":"bd9ca328-d553-11ed-ba76-dc4f890cfe62","call_identifier":"H2020"},{"_id":"34def286-11ca-11ed-8bc3-da5948e1613c","grant_number":"Z00422","name":"Wittgenstein Award - Monika Henzinger"},{"grant_number":"P33775 ","name":"Fast Algorithms for a Reactive Network Layer","_id":"bd9e3a2e-d553-11ed-ba76-8aa684ce17fe"}],"conference":{"location":"Honolulu, Hawaii, HI, United States","start_date":"2023-07-23","name":"ICML: International Conference on Machine Learning","end_date":"2023-07-29"},"author":[{"full_name":"Fichtenberger, Hendrik","first_name":"Hendrik","last_name":"Fichtenberger"},{"id":"540c9bbd-f2de-11ec-812d-d04a5be85630","full_name":"Henzinger, Monika H","orcid":"0000-0002-5008-6530","last_name":"Henzinger","first_name":"Monika H"},{"full_name":"Upadhyay, Jalaj","first_name":"Jalaj","last_name":"Upadhyay"}],"date_published":"2023-07-30T00:00:00Z","article_processing_charge":"No","alternative_title":["PMLR"],"date_updated":"2025-07-15T12:51:52Z","scopus_import":"1","quality_controlled":"1","volume":202,"page":"10072-10092","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","_id":"14462","year":"2023","status":"public","oa":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.","citation":{"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.","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.","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.","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.","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.","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.","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."},"publication_identifier":{"eissn":["2640-3498"]},"publication":"Proceedings of the 40th International Conference on Machine Learning","department":[{"_id":"MoHe"}],"title":"Constant matters: Fine-grained error bound on differentially private continual observation","publisher":"ML Research Press","date_created":"2023-10-29T23:01:17Z","ec_funded":1,"oa_version":"Published Version","abstract":[{"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.","lang":"eng"}]}]