---
_id: '14447'
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."
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.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Kristýna
full_name: Bieleszová, Kristýna
last_name: Bieleszová
- first_name: Pavel
full_name: Hladík, Pavel
last_name: Hladík
- first_name: Martin
full_name: Kubala, Martin
last_name: Kubala
- first_name: Richard
full_name: Napier, Richard
last_name: Napier
- first_name: Federica
full_name: Brunoni, Federica
last_name: Brunoni
- first_name: Zuzana
full_name: Gelová, Zuzana
id: 0AE74790-0E0B-11E9-ABC7-1ACFE5697425
last_name: Gelová
orcid: 0000-0003-4783-1752
- first_name: Lukas
full_name: Fiedler, Lukas
id: 7c417475-8972-11ed-ae7b-8b674ca26986
last_name: Fiedler
- first_name: Ivan
full_name: Kulich, Ivan
id: 57a1567c-8314-11eb-9063-c9ddc3451a54
last_name: Kulich
- first_name: Miroslav
full_name: Strnad, Miroslav
last_name: Strnad
- first_name: Karel
full_name: Doležal, Karel
last_name: Doležal
- first_name: Ondřej
full_name: Novák, Ondřej
last_name: Novák
- first_name: Jiří
full_name: Friml, Jiří
id: 4159519E-F248-11E8-B48F-1D18A9856A87
last_name: Friml
orcid: 0000-0002-8302-7596
- first_name: Asta
full_name: Žukauskaitė, Asta
last_name: Žukauskaitė
citation:
ama: 'Bieleszová K, Hladík P, Kubala M, et al. New fluorescent auxin derivatives:
anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant
Growth Regulation. 2023. doi:10.1007/s10725-023-01083-0'
apa: 'Bieleszová, K., Hladík, P., Kubala, M., Napier, R., Brunoni, F., Gelová, Z.,
… Žukauskaitė, A. (2023). New fluorescent auxin derivatives: anti-auxin activity
and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation.
Springer Nature. https://doi.org/10.1007/s10725-023-01083-0'
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.'
ieee: 'K. Bieleszová et al., “New fluorescent auxin derivatives: anti-auxin
activity and accumulation patterns in Arabidopsis thaliana,” Plant Growth Regulation.
Springer Nature, 2023.'
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.'
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.'
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).
date_created: 2023-10-22T22:01:15Z
date_published: 2023-10-13T00:00:00Z
date_updated: 2023-12-13T13:08:25Z
day: '13'
department:
- _id: JiFr
doi: 10.1007/s10725-023-01083-0
external_id:
isi:
- '001084334300001'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s10725-023-01083-0
month: '10'
oa: 1
oa_version: Published Version
publication: Plant Growth Regulation
publication_identifier:
eissn:
- 1573-5087
issn:
- 0167-6903
publication_status: epub_ahead
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns
in Arabidopsis thaliana'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14448'
abstract:
- lang: eng
text: We consider the problem of solving LP relaxations of MAP-MRF inference problems,
and in particular the method proposed recently in [16], [35]. As a key computational
subroutine, it uses a variant of the Frank-Wolfe (FW) method to minimize a smooth
convex function over a combinatorial polytope. We propose an efficient implementation
of this subroutine based on in-face Frank-Wolfe directions, introduced in [4]
in a different context. More generally, we define an abstract data structure for
a combinatorial subproblem that enables in-face FW directions, and describe its
specialization for tree-structured MAP-MRF inference subproblems. Experimental
results indicate that the resulting method is the current state-of-art LP solver
for some classes of problems. Our code is available at pub.ist.ac.at/~vnk/papers/IN-FACE-FW.html.
article_processing_charge: No
arxiv: 1
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
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'
apa: 'Kolmogorov, V. (2023). Solving relaxations of MAP-MRF problems: Combinatorial
in-face Frank-Wolfe directions. In Proceedings of the IEEE Computer Society
Conference on Computer Vision and Pattern Recognition (Vol. 2023, pp. 11980–11989).
Vancouver, Canada: IEEE. https://doi.org/10.1109/CVPR52729.2023.01153'
chicago: 'Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial
in-Face Frank-Wolfe Directions.” In Proceedings of the IEEE Computer Society
Conference on Computer Vision and Pattern Recognition, 2023:11980–89. IEEE,
2023. https://doi.org/10.1109/CVPR52729.2023.01153.'
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.'
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.'
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.'
short: V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on
Computer Vision and Pattern Recognition, IEEE, 2023, pp. 11980–11989.
conference:
end_date: 2023-06-24
location: Vancouver, Canada
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2023-06-17
date_created: 2023-10-22T22:01:16Z
date_published: 2023-08-22T00:00:00Z
date_updated: 2023-10-31T12:01:24Z
day: '22'
department:
- _id: VlKo
doi: 10.1109/CVPR52729.2023.01153
external_id:
arxiv:
- '2010.09567'
intvolume: ' 2023'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.2010.09567'
month: '08'
oa: 1
oa_version: Preprint
page: 11980-11989
publication: Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition
publication_identifier:
isbn:
- '9798350301298'
issn:
- 1063-6919
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe
directions'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2023
year: '2023'
...
---
_id: '14449'
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.
acknowledgement: "This study is based upon work from COST Action ML4Microbiome “Statistical
and machine learning techniques in human microbiome studies” (CA18131), supported
by COST (European Cooperation in Science and Technology), www.cost.eu. MB acknowledges
support through the Metagenopolis grant ANR-11-DPBS-0001. IM-I acknowledges support
by the “Miguel Servet Type II” program (CPII21/00013) of the ISCIII-Madrid (Spain),
co-financed by the FEDER.\r\nThe authors are grateful to all COST Action CA18131
“Statistical and machine learning techniques in human microbiome studies” members
for their contribution to the COST Action objectives, and to COST (European Cooperation
in Science and Technology) for the economic support, www.cost.eu. WG2 and WG3 thank
Emmanuelle Le Chatelier and Pauline Barbet (Université Paris-Saclay, INRAE, MetaGenoPolis,
78350, Jouy-en-Josas, France) for preparing the shotgun CRC benchmark dataset."
article_number: '1257002'
article_processing_charge: Yes
article_type: original
author:
- first_name: Domenica
full_name: D’Elia, Domenica
last_name: D’Elia
- first_name: Jaak
full_name: Truu, Jaak
last_name: Truu
- first_name: Leo
full_name: Lahti, Leo
last_name: Lahti
- first_name: Magali
full_name: Berland, Magali
last_name: Berland
- first_name: Georgios
full_name: Papoutsoglou, Georgios
last_name: Papoutsoglou
- first_name: Michelangelo
full_name: Ceci, Michelangelo
last_name: Ceci
- first_name: Aldert
full_name: Zomer, Aldert
last_name: Zomer
- first_name: Marta B.
full_name: Lopes, Marta B.
last_name: Lopes
- first_name: Eliana
full_name: Ibrahimi, Eliana
last_name: Ibrahimi
- first_name: Aleksandra
full_name: Gruca, Aleksandra
last_name: Gruca
- first_name: Alina
full_name: Nechyporenko, Alina
last_name: Nechyporenko
- first_name: Marcus
full_name: Frohme, Marcus
last_name: Frohme
- first_name: Thomas
full_name: Klammsteiner, Thomas
last_name: Klammsteiner
- first_name: Enrique Carrillo De Santa
full_name: Pau, Enrique Carrillo De Santa
last_name: Pau
- first_name: Laura Judith
full_name: Marcos-Zambrano, Laura Judith
last_name: Marcos-Zambrano
- first_name: Karel
full_name: Hron, Karel
last_name: Hron
- first_name: Gianvito
full_name: Pio, Gianvito
last_name: Pio
- first_name: Andrea
full_name: Simeon, Andrea
last_name: Simeon
- first_name: Ramona
full_name: Suharoschi, Ramona
last_name: Suharoschi
- first_name: Isabel
full_name: Moreno-Indias, Isabel
last_name: Moreno-Indias
- first_name: Andriy
full_name: Temko, Andriy
last_name: Temko
- first_name: Miroslava
full_name: Nedyalkova, Miroslava
last_name: Nedyalkova
- first_name: Elena Simona
full_name: Apostol, Elena Simona
last_name: Apostol
- first_name: Ciprian Octavian
full_name: Truică, Ciprian Octavian
last_name: Truică
- first_name: Rajesh
full_name: Shigdel, Rajesh
last_name: Shigdel
- first_name: Jasminka Hasić
full_name: Telalović, Jasminka Hasić
last_name: Telalović
- first_name: Erik
full_name: Bongcam-Rudloff, Erik
last_name: Bongcam-Rudloff
- first_name: Piotr
full_name: Przymus, Piotr
last_name: Przymus
- first_name: Naida Babić
full_name: Jordamović, Naida Babić
last_name: Jordamović
- first_name: Laurent
full_name: Falquet, Laurent
last_name: Falquet
- first_name: Sonia
full_name: Tarazona, Sonia
last_name: Tarazona
- first_name: Alexia
full_name: Sampri, Alexia
last_name: Sampri
- first_name: Gaetano
full_name: Isola, Gaetano
last_name: Isola
- first_name: David
full_name: Pérez-Serrano, David
last_name: Pérez-Serrano
- first_name: Vladimir
full_name: Trajkovik, Vladimir
last_name: Trajkovik
- first_name: Lubos
full_name: Klucar, Lubos
last_name: Klucar
- first_name: Tatjana
full_name: Loncar-Turukalo, Tatjana
last_name: Loncar-Turukalo
- first_name: Aki S.
full_name: Havulinna, Aki S.
last_name: Havulinna
- first_name: Christian
full_name: Jansen, Christian
id: 837b2259-bcc9-11ed-a196-ae55927bc6e2
last_name: Jansen
- first_name: Randi J.
full_name: Bertelsen, Randi J.
last_name: Bertelsen
- first_name: Marcus Joakim
full_name: Claesson, Marcus Joakim
last_name: Claesson
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'
apa: 'D’Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M.,
… Claesson, M. J. (2023). Advancing microbiome research with machine learning:
Key findings from the ML4Microbiome COST action. Frontiers in Microbiology.
Frontiers. https://doi.org/10.3389/fmicb.2023.1257002'
chicago: 'D’Elia, Domenica, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou,
Michelangelo Ceci, Aldert Zomer, et al. “Advancing Microbiome Research with Machine
Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology.
Frontiers, 2023. https://doi.org/10.3389/fmicb.2023.1257002.'
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.'
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.'
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.'
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).
date_created: 2023-10-22T22:01:16Z
date_published: 2023-09-25T00:00:00Z
date_updated: 2023-12-13T13:07:21Z
day: '25'
ddc:
- '000'
department:
- _id: ScienComp
doi: 10.3389/fmicb.2023.1257002
external_id:
isi:
- '001080536000001'
pmid:
- '37808321'
file:
- access_level: open_access
checksum: 6c0acdd8fa111a699826957b8dff19d5
content_type: application/pdf
creator: dernst
date_created: 2023-10-30T13:38:48Z
date_updated: 2023-10-30T13:38:48Z
file_id: '14471'
file_name: 2023_FrontiersMicrobiology_DElia.pdf
file_size: 505078
relation: main_file
success: 1
file_date_updated: 2023-10-30T13:38:48Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
publication: Frontiers in Microbiology
publication_identifier:
eissn:
- 1664-302X
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Advancing microbiome research with machine learning: Key findings from the
ML4Microbiome COST action'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2023'
...
---
_id: '14451'
abstract:
- lang: eng
text: 'We investigate the potential of Multi-Objective, Deep Reinforcement Learning
for stock and cryptocurrency single-asset trading: in particular, we consider
a Multi-Objective algorithm which generalizes the reward functions and discount
factor (i.e., these components are not specified a priori, but incorporated in
the learning process). Firstly, using several important assets (BTCUSD, ETHUSDT,
XRPUSDT, AAPL, SPY, NIFTY50), we verify the reward generalization property of
the proposed Multi-Objective algorithm, and provide preliminary statistical evidence
showing increased predictive stability over the corresponding Single-Objective
strategy. Secondly, we show that the Multi-Objective algorithm has a clear edge
over the corresponding Single-Objective strategy when the reward mechanism is
sparse (i.e., when non-null feedback is infrequent over time). Finally, we discuss
the generalization properties with respect to the discount factor. The entirety
of our code is provided in open-source format.'
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.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Federico
full_name: Cornalba, Federico
id: 2CEB641C-A400-11E9-A717-D712E6697425
last_name: Cornalba
orcid: 0000-0002-6269-5149
- first_name: Constantin
full_name: Disselkamp, Constantin
last_name: Disselkamp
- first_name: Davide
full_name: Scassola, Davide
last_name: Scassola
- first_name: Christopher
full_name: Helf, Christopher
last_name: Helf
citation:
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'
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'
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.'
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.'
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.'
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).
date_created: 2023-10-22T22:01:16Z
date_published: 2023-10-05T00:00:00Z
date_updated: 2023-10-31T10:58:28Z
day: '05'
department:
- _id: JuFi
doi: 10.1007/s00521-023-09033-7
ec_funded: 1
external_id:
arxiv:
- '2203.04579'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s00521-023-09033-7
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neural Computing and Applications
publication_identifier:
eissn:
- 1433-3058
issn:
- 0941-0643
publication_status: epub_ahead
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Multi-objective reward generalization: improving performance of Deep Reinforcement
Learning for applications in single-asset trading'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14452'
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.
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.
article_number: iyad133
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Alison M.
full_name: Etheridge, Alison M.
last_name: Etheridge
- first_name: Amandine
full_name: Véber, Amandine
last_name: Véber
citation:
ama: Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics.
2023;225(2). doi:10.1093/genetics/iyad133
apa: Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal
model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133
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.
ista: Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance.
Genetics. 225(2), iyad133.
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.
short: N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).
date_created: 2023-10-29T23:01:15Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2025-05-28T11:42:48Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1093/genetics/iyad133
ec_funded: 1
external_id:
arxiv:
- '2211.03515'
file:
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checksum: 3f65b1fbe813e2f4dbb5d2b5e891844a
content_type: application/pdf
creator: dernst
date_created: 2023-10-30T12:57:53Z
date_updated: 2023-10-30T12:57:53Z
file_id: '14469'
file_name: 2023_Genetics_Barton.pdf
file_size: 1439032
relation: main_file
success: 1
file_date_updated: 2023-10-30T12:57:53Z
has_accepted_license: '1'
intvolume: ' 225'
issue: '2'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
grant_number: '101055327'
name: Understanding the evolution of continuous genomes
publication: Genetics
publication_identifier:
eissn:
- 1943-2631
issn:
- 0016-6731
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
related_material:
record:
- id: '12949'
relation: research_data
status: public
scopus_import: '1'
status: public
title: The infinitesimal model with dominance
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 225
year: '2023'
...
---
_id: '14453'
abstract:
- lang: eng
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.
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.
article_number: e2022MS003477
article_processing_charge: Yes
article_type: original
author:
- first_name: Sophie
full_name: Abramian, Sophie
last_name: Abramian
- first_name: Caroline J
full_name: Muller, Caroline J
id: f978ccb0-3f7f-11eb-b193-b0e2bd13182b
last_name: Muller
orcid: 0000-0001-5836-5350
- first_name: Camille
full_name: Risi, Camille
last_name: Risi
citation:
ama: Abramian S, Muller CJ, Risi C. Extreme precipitation in tropical squall lines.
Journal of Advances in Modeling Earth Systems. 2023;15(10). doi:10.1029/2022MS003477
apa: Abramian, S., Muller, C. J., & Risi, C. (2023). Extreme precipitation in
tropical squall lines. Journal of Advances in Modeling Earth Systems. Wiley.
https://doi.org/10.1029/2022MS003477
chicago: Abramian, Sophie, Caroline J Muller, and Camille Risi. “Extreme Precipitation
in Tropical Squall Lines.” Journal of Advances in Modeling Earth Systems.
Wiley, 2023. https://doi.org/10.1029/2022MS003477.
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.
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.
short: S. Abramian, C.J. Muller, C. Risi, Journal of Advances in Modeling Earth
Systems 15 (2023).
date_created: 2023-10-29T23:01:15Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2023-12-13T13:06:40Z
day: '01'
ddc:
- '550'
department:
- _id: CaMu
doi: 10.1029/2022MS003477
ec_funded: 1
external_id:
isi:
- '001084933600001'
file:
- access_level: open_access
checksum: 43e6a1a35b663843c7d3f8d0caaca1a5
content_type: application/pdf
creator: dernst
date_created: 2023-10-30T13:31:42Z
date_updated: 2023-10-30T13:31:42Z
file_id: '14470'
file_name: 2023_JAMES_Abramian.pdf
file_size: 1975210
relation: main_file
success: 1
file_date_updated: 2023-10-30T13:31:42Z
has_accepted_license: '1'
intvolume: ' 15'
isi: 1
issue: '10'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 629205d8-2b32-11ec-9570-e1356ff73576
call_identifier: H2020
grant_number: '805041'
name: organization of CLoUdS, and implications of Tropical cyclones and for the
Energetics of the tropics, in current and waRming climate
publication: Journal of Advances in Modeling Earth Systems
publication_identifier:
eissn:
- 1942-2466
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Extreme precipitation in tropical squall lines
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 15
year: '2023'
...
---
_id: '14454'
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.
acknowledgement: 'This work is supported by the European Research Council under Grant
No.: ERC-2020-AdG 101020093.'
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Konstantin
full_name: Kueffner, Konstantin
id: 8121a2d0-dc85-11ea-9058-af578f3b4515
last_name: Kueffner
orcid: 0000-0001-8974-2542
- first_name: Kaushik
full_name: Mallik, Kaushik
id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598
last_name: Mallik
orcid: 0000-0001-9864-7475
citation:
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'
apa: 'Henzinger, T. A., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic
fairness under partial observations. In 23rd International Conference on Runtime
Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature.
https://doi.org/10.1007/978-3-031-44267-4_15'
chicago: Henzinger, Thomas A, Konstantin Kueffner, and Kaushik Mallik. “Monitoring
Algorithmic Fairness under Partial Observations.” In 23rd International Conference
on Runtime Verification, 14245:291–311. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_15.
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.
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.'
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.
short: T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference
on Runtime Verification, Springer Nature, 2023, pp. 291–311.
conference:
end_date: 2023-10-06
location: Thessaloniki, Greece
name: 'RV: Conference on Runtime Verification'
start_date: 2023-10-03
date_created: 2023-10-29T23:01:15Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2023-10-31T11:48:20Z
day: '01'
department:
- _id: ToHe
doi: 10.1007/978-3-031-44267-4_15
ec_funded: 1
external_id:
arxiv:
- '2308.00341'
intvolume: ' 14245'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2308.00341
month: '10'
oa: 1
oa_version: Preprint
page: 291-311
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: 23rd International Conference on Runtime Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031442667'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Monitoring algorithmic fairness under partial observations
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14245
year: '2023'
...
---
_id: '14455'
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.
article_number: '1287879'
article_processing_charge: Yes
article_type: letter_note
author:
- first_name: Antonio
full_name: Narzisi, Antonio
last_name: Narzisi
- first_name: Alycia
full_name: Halladay, Alycia
last_name: Halladay
- first_name: Gabriele
full_name: Masi, Gabriele
last_name: Masi
- first_name: Gaia
full_name: Novarino, Gaia
id: 3E57A680-F248-11E8-B48F-1D18A9856A87
last_name: Novarino
orcid: 0000-0002-7673-7178
- first_name: Catherine
full_name: Lord, Catherine
last_name: Lord
citation:
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'
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.'
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.'
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.'
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.'
short: A. Narzisi, A. Halladay, G. Masi, G. Novarino, C. Lord, Frontiers in Psychiatry
14 (2023).
date_created: 2023-10-29T23:01:16Z
date_published: 2023-10-03T00:00:00Z
date_updated: 2023-12-13T13:06:07Z
day: '03'
ddc:
- '570'
department:
- _id: GaNo
doi: 10.3389/fpsyt.2023.1287879
external_id:
isi:
- '001084841700001'
pmid:
- '37854442'
file:
- access_level: open_access
checksum: 0a76373e9a4c0fc199f80380de257e86
content_type: application/pdf
creator: dernst
date_created: 2023-10-30T12:48:40Z
date_updated: 2023-10-30T12:48:40Z
file_id: '14468'
file_name: 2023_FrontiersPsychiatry_Narzisi.pdf
file_size: 147878
relation: main_file
success: 1
file_date_updated: 2023-10-30T12:48:40Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
pmid: 1
publication: Frontiers in Psychiatry
publication_identifier:
eissn:
- 1664-0640
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Tempering expectations: Considerations on the current state of stem cells
therapy for autism treatment'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2023'
...
---
_id: '14456'
abstract:
- lang: eng
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.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Jan Matyáš
full_name: Křišťan, Jan Matyáš
last_name: Křišťan
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
citation:
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'
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'
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.
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.
conference:
end_date: 2023-09-21
location: Trier, Germany
name: 'FCT: Fundamentals of Computation Theory'
start_date: 2023-09-18
date_created: 2023-10-29T23:01:16Z
date_published: 2023-09-21T00:00:00Z
date_updated: 2024-01-22T08:10:49Z
day: '21'
department:
- _id: KrCh
doi: 10.1007/978-3-031-43587-4_24
external_id:
arxiv:
- '2307.10847'
intvolume: ' 14292'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2307.10847
month: '09'
oa: 1
oa_version: Preprint
page: 333-347
publication: 24th International Symposium on Fundamentals of Computation Theory
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031435867'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1007/978-3-031-43587-4_31
scopus_import: '1'
status: public
title: Shortest dominating set reconfiguration under token sliding
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14292
year: '2023'
...
---
_id: '14457'
abstract:
- lang: eng
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"
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Charlotte
full_name: Hoffmann, Charlotte
id: 0f78d746-dc7d-11ea-9b2f-83f92091afe7
last_name: Hoffmann
orcid: 0000-0003-2027-5549
- first_name: Mark
full_name: Simkin, Mark
last_name: Simkin
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'
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'
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.
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.'
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.
short: C. Hoffmann, M. Simkin, in:, 8th International Conference on Cryptology and
Information Security in Latin America, Springer Nature, 2023, pp. 215–228.
conference:
end_date: 2023-10-06
location: Quito, Ecuador
name: 'LATINCRYPT: Conference on Cryptology and Information Security in Latin America'
start_date: 2023-10-03
date_created: 2023-10-29T23:01:16Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2023-10-31T11:43:12Z
day: '01'
department:
- _id: KrPi
doi: 10.1007/978-3-031-44469-2_11
intvolume: ' 14168'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2023/1017
month: '10'
oa: 1
oa_version: Preprint
page: 215-228
publication: 8th International Conference on Cryptology and Information Security in
Latin America
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031444685'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Stronger lower bounds for leakage-resilient secret sharing
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14168
year: '2023'
...
---
_id: '14458'
abstract:
- lang: eng
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.'
acknowledged_ssus:
- _id: ScienComp
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.
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately
pruned in one-shot. In: Proceedings of the 40th International Conference on
Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.'
apa: 'Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models
can be accurately pruned in one-shot. In Proceedings of the 40th International
Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii,
HI, United States: ML Research Press.'
chicago: 'Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language
Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International
Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.'
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.'
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.'
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.'
short: E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference
on Machine Learning, ML Research Press, 2023, pp. 10323–10337.
conference:
end_date: 2023-07-29
location: Honolulu, Hawaii, HI, United States
name: 'ICML: International Conference on Machine Learning'
start_date: 2023-07-23
date_created: 2023-10-29T23:01:16Z
date_published: 2023-07-30T00:00:00Z
date_updated: 2023-10-31T09:59:42Z
day: '30'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2301.00774'
intvolume: ' 202'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2301.00774
month: '07'
oa: 1
oa_version: Preprint
page: 10323-10337
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the 40th International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'SparseGPT: Massive language models can be accurately pruned in one-shot'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2023'
...
---
_id: '14459'
abstract:
- lang: eng
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.
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).
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Aleksandr
full_name: Shevchenko, Aleksandr
id: F2B06EC2-C99E-11E9-89F0-752EE6697425
last_name: Shevchenko
- first_name: Kevin
full_name: Kögler, Kevin
id: 94ec913c-dc85-11ea-9058-e5051ab2428b
last_name: Kögler
- first_name: Hamed
full_name: Hassani, Hamed
last_name: Hassani
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
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.'
apa: 'Shevchenko, A., Kögler, K., Hassani, H., & Mondelli, M. (2023). Fundamental
limits of two-layer autoencoders, and achieving them with gradient methods. In
Proceedings of the 40th International Conference on Machine Learning (Vol.
202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.'
chicago: Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli.
“Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient
Methods.” In Proceedings of the 40th International Conference on Machine Learning,
202:31151–209. ML Research Press, 2023.
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.
ista: 'Shevchenko A, Kögler K, Hassani H, Mondelli M. 2023. Fundamental limits of
two-layer autoencoders, and achieving them with gradient methods. Proceedings
of the 40th International Conference on Machine Learning. ICML: International
Conference on Machine Learning, PMLR, vol. 202, 31151–31209.'
mla: Shevchenko, Aleksandr, et al. “Fundamental Limits of Two-Layer Autoencoders,
and Achieving Them with Gradient Methods.” Proceedings of the 40th International
Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 31151–209.
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.
conference:
end_date: 2023-07-29
location: Honolulu, Hawaii, HI, United States
name: 'ICML: International Conference on Machine Learning'
start_date: 2023-07-23
date_created: 2023-10-29T23:01:17Z
date_published: 2023-07-30T00:00:00Z
date_updated: 2024-09-10T13:03:19Z
day: '30'
department:
- _id: MaMo
- _id: DaAl
external_id:
arxiv:
- '2212.13468'
intvolume: ' 202'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2212.13468
month: '07'
oa: 1
oa_version: Preprint
page: 31151-31209
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: Proceedings of the 40th International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Fundamental limits of two-layer autoencoders, and achieving them with gradient
methods
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2023'
...
---
_id: '14460'
abstract:
- lang: eng
text: We provide an efficient implementation of the backpropagation algorithm, specialized
to the case where the weights of the neural network being trained are sparse.
Our algorithm is general, as it applies to arbitrary (unstructured) sparsity and
common layer types (e.g., convolutional or linear). We provide a fast vectorized
implementation on commodity CPUs, and show that it can yield speedups in end-to-end
runtime experiments, both in transfer learning using already-sparsified networks,
and in training sparse networks from scratch. Thus, our results provide the first
support for sparse training on commodity hardware.
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. '
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Mahdi
full_name: Nikdan, Mahdi
id: 66374281-f394-11eb-9cf6-869147deecc0
last_name: Nikdan
- first_name: Tommaso
full_name: Pegolotti, Tommaso
last_name: Pegolotti
- first_name: Eugenia B
full_name: Iofinova, Eugenia B
id: f9a17499-f6e0-11ea-865d-fdf9a3f77117
last_name: Iofinova
orcid: 0000-0002-7778-3221
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
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.'
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.'
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.'
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.'
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.'
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.
conference:
end_date: 2023-07-29
location: Honolulu, Hawaii, HI, United States
name: 'ICML: International Conference on Machine Learning'
start_date: 2023-07-23
date_created: 2023-10-29T23:01:17Z
date_published: 2023-07-30T00:00:00Z
date_updated: 2023-10-31T09:33:51Z
day: '30'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2302.04852'
intvolume: ' 202'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2302.04852
month: '07'
oa: 1
oa_version: Preprint
page: 26215-26227
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the 40th International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'SparseProp: Efficient sparse backpropagation for faster training of neural
networks at the edge'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2023'
...
---
_id: '14461'
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.'
acknowledged_ssus:
- _id: ScienComp
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).
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Ilia
full_name: Markov, Ilia
id: D0CF4148-C985-11E9-8066-0BDEE5697425
last_name: Markov
- first_name: Adrian
full_name: Vladu, Adrian
last_name: Vladu
- first_name: Qi
full_name: Guo, Qi
last_name: Guo
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
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.'
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.'
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.
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.
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.
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.
conference:
end_date: 2023-07-29
location: Honolulu, Hawaii, HI, United States
name: 'ICML: International Conference on Machine Learning'
start_date: 2023-07-23
date_created: 2023-10-29T23:01:17Z
date_published: 2023-07-30T00:00:00Z
date_updated: 2023-10-31T09:40:45Z
day: '30'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2302.02390'
intvolume: ' 202'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2302.02390
month: '07'
oa: 1
oa_version: Preprint
page: 24020-24044
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the 40th International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantized distributed training of large models with convergence guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2023'
...
---
_id: '14462'
abstract:
- lang: eng
text: "We study fine-grained error bounds for differentially private algorithms
for counting under continual observation. Our main insight is that the matrix
mechanism when using lower-triangular matrices can be used in the continual observation
model. More specifically, we give an explicit factorization for the counting matrix
Mcount and upper bound the error explicitly. We also give a fine-grained analysis,
specifying the exact constant in the upper bound. Our analysis is based on upper
and lower bounds of the completely bounded norm (cb-norm) of Mcount\r\n. Along
the way, we improve the best-known bound of 28 years by Mathias (SIAM Journal
on Matrix Analysis and Applications, 1993) on the cb-norm of Mcount for a large
range of the dimension of Mcount. Furthermore, we are the first to give concrete
error bounds for various problems under continual observation such as binary counting,
maintaining a histogram, releasing an approximately cut-preserving synthetic graph,
many graph-based statistics, and substring and episode counting. Finally, we note
that our result can be used to get a fine-grained error bound for non-interactive
local learning and the first lower bounds on the additive error for (ϵ,δ)-differentially-private
counting under continual observation. Subsequent to this work, Henzinger et al.
(SODA, 2023) showed that our factorization also achieves fine-grained mean-squared
error."
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."
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Hendrik
full_name: Fichtenberger, Hendrik
last_name: Fichtenberger
- first_name: Monika H
full_name: Henzinger, Monika H
id: 540c9bbd-f2de-11ec-812d-d04a5be85630
last_name: Henzinger
orcid: 0000-0002-5008-6530
- first_name: Jalaj
full_name: Upadhyay, Jalaj
last_name: Upadhyay
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.'
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.'
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.'
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.'
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.
conference:
end_date: 2023-07-29
location: Honolulu, Hawaii, HI, United States
name: 'ICML: International Conference on Machine Learning'
start_date: 2023-07-23
date_created: 2023-10-29T23:01:17Z
date_published: 2023-07-30T00:00:00Z
date_updated: 2025-07-15T12:51:52Z
day: '30'
department:
- _id: MoHe
ec_funded: 1
intvolume: ' 202'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.mlr.press/v202/fichtenberger23a/fichtenberger23a.pdf
month: '07'
oa: 1
oa_version: Published Version
page: 10072-10092
project:
- _id: bd9ca328-d553-11ed-ba76-dc4f890cfe62
call_identifier: H2020
grant_number: '101019564'
name: The design and evaluation of modern fully dynamic data structures
- _id: 34def286-11ca-11ed-8bc3-da5948e1613c
grant_number: Z00422
name: Wittgenstein Award - Monika Henzinger
- _id: bd9e3a2e-d553-11ed-ba76-8aa684ce17fe
grant_number: 'P33775 '
name: Fast Algorithms for a Reactive Network Layer
publication: Proceedings of the 40th International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Constant matters: Fine-grained error bound on differentially private continual
observation'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2023'
...
---
_id: '14463'
abstract:
- lang: eng
text: Inversions are thought to play a key role in adaptation and speciation, suppressing
recombination between diverging populations. Genes influencing adaptive traits
cluster in inversions, and changes in inversion frequencies are associated with
environmental differences. However, in many organisms, it is unclear if inversions
are geographically and taxonomically widespread. The intertidal snail, Littorina
saxatilis, is one such example. Strong associations between putative polymorphic
inversions and phenotypic differences have been demonstrated between two ecotypes
of L. saxatilis in Sweden and inferred elsewhere, but no direct evidence for inversion
polymorphism currently exists across the species range. Using whole genome data
from 107 snails, most inversion polymorphisms were found to be widespread across
the species range. The frequencies of some inversion arrangements were significantly
different among ecotypes, suggesting a parallel adaptive role. Many inversions
were also polymorphic in the sister species, L. arcana, hinting at an ancient
origin.
acknowledgement: We would like to thank members of the Littorina team for their advice
and feedback during this project. In particular, we thank Alan Le Moan, who inspired
us to look at heterozygosity differences to identify inversions, and Katherine Hearn
for helping with the PCA scripts. We thank Edinburgh Genomics for library preparation
and sequencing. Sample collections, sequencing and data preparation were supported
by the European Research Council (ERC-2015-AdG-693030- BARRIERS) and the Natural
Environment Research Council (NE/P001610/1). The analysis was supported by the Swedish
Research Council (vetenskaprådet; 2018-03695_VR) and the Portuguese Foundation for
Science and Technology (Fundación para a Ciência e Tecnologia) through a research
project (PTDC/BIA-EVL/1614/2021) and CEEC contract (2020.00275.CEECIND).
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: James
full_name: Reeve, James
last_name: Reeve
- first_name: Roger K.
full_name: Butlin, Roger K.
last_name: Butlin
- first_name: Eva L.
full_name: Koch, Eva L.
last_name: Koch
- first_name: Sean
full_name: Stankowski, Sean
id: 43161670-5719-11EA-8025-FABC3DDC885E
last_name: Stankowski
- first_name: Rui
full_name: Faria, Rui
last_name: Faria
citation:
ama: Reeve J, Butlin RK, Koch EL, Stankowski S, Faria R. Chromosomal inversion polymorphisms
are widespread across the species ranges of rough periwinkles (Littorina saxatilis
and L. arcana). Molecular Ecology. 2023. doi:10.1111/mec.17160
apa: Reeve, J., Butlin, R. K., Koch, E. L., Stankowski, S., & Faria, R. (2023).
Chromosomal inversion polymorphisms are widespread across the species ranges of
rough periwinkles (Littorina saxatilis and L. arcana). Molecular Ecology.
Wiley. https://doi.org/10.1111/mec.17160
chicago: Reeve, James, Roger K. Butlin, Eva L. Koch, Sean Stankowski, and Rui Faria.
“Chromosomal Inversion Polymorphisms Are Widespread across the Species Ranges
of Rough Periwinkles (Littorina Saxatilis and L. Arcana).” Molecular Ecology.
Wiley, 2023. https://doi.org/10.1111/mec.17160.
ieee: J. Reeve, R. K. Butlin, E. L. Koch, S. Stankowski, and R. Faria, “Chromosomal
inversion polymorphisms are widespread across the species ranges of rough periwinkles
(Littorina saxatilis and L. arcana),” Molecular Ecology. Wiley, 2023.
ista: Reeve J, Butlin RK, Koch EL, Stankowski S, Faria R. 2023. Chromosomal inversion
polymorphisms are widespread across the species ranges of rough periwinkles (Littorina
saxatilis and L. arcana). Molecular Ecology.
mla: Reeve, James, et al. “Chromosomal Inversion Polymorphisms Are Widespread across
the Species Ranges of Rough Periwinkles (Littorina Saxatilis and L. Arcana).”
Molecular Ecology, Wiley, 2023, doi:10.1111/mec.17160.
short: J. Reeve, R.K. Butlin, E.L. Koch, S. Stankowski, R. Faria, Molecular Ecology
(2023).
date_created: 2023-10-29T23:01:17Z
date_published: 2023-10-16T00:00:00Z
date_updated: 2023-12-13T13:05:27Z
day: '16'
department:
- _id: NiBa
doi: 10.1111/mec.17160
external_id:
isi:
- '001085119000001'
pmid:
- '37843465'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1111/mec.17160
month: '10'
oa: 1
oa_version: Published Version
pmid: 1
publication: Molecular Ecology
publication_identifier:
eissn:
- 1365-294X
issn:
- 0962-1083
publication_status: epub_ahead
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Chromosomal inversion polymorphisms are widespread across the species ranges
of rough periwinkles (Littorina saxatilis and L. arcana)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14464'
abstract:
- lang: eng
text: 'Given a triangle Δ, we study the problem of determining the smallest enclosing
and largest embedded isosceles triangles of Δ with respect to area and perimeter.
This problem was initially posed by Nandakumar [17, 22] and was first studied
by Kiss, Pach, and Somlai [13], who showed that if Δ′ is the smallest area isosceles
triangle containing Δ, then Δ′ and Δ share a side and an angle. In the present
paper, we prove that for any triangle Δ, every maximum area isosceles triangle
embedded in Δ and every maximum perimeter isosceles triangle embedded in Δ shares
a side and an angle with Δ. Somewhat surprisingly, the case of minimum perimeter
enclosing triangles is different: there are infinite families of triangles Δ whose
minimum perimeter isosceles containers do not share a side and an angle with Δ.'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Áron
full_name: Ambrus, Áron
last_name: Ambrus
- first_name: Mónika
full_name: Csikós, Mónika
last_name: Csikós
- first_name: Gergely
full_name: Kiss, Gergely
last_name: Kiss
- first_name: János
full_name: Pach, János
id: E62E3130-B088-11EA-B919-BF823C25FEA4
last_name: Pach
- first_name: Gábor
full_name: Somlai, Gábor
last_name: Somlai
citation:
ama: Ambrus Á, Csikós M, Kiss G, Pach J, Somlai G. Optimal embedded and enclosing
isosceles triangles. International Journal of Foundations of Computer Science.
2023;34(7):737-760. doi:10.1142/S012905412342008X
apa: Ambrus, Á., Csikós, M., Kiss, G., Pach, J., & Somlai, G. (2023). Optimal
embedded and enclosing isosceles triangles. International Journal of Foundations
of Computer Science. World Scientific Publishing. https://doi.org/10.1142/S012905412342008X
chicago: Ambrus, Áron, Mónika Csikós, Gergely Kiss, János Pach, and Gábor Somlai.
“Optimal Embedded and Enclosing Isosceles Triangles.” International Journal
of Foundations of Computer Science. World Scientific Publishing, 2023. https://doi.org/10.1142/S012905412342008X.
ieee: Á. Ambrus, M. Csikós, G. Kiss, J. Pach, and G. Somlai, “Optimal embedded and
enclosing isosceles triangles,” International Journal of Foundations of Computer
Science, vol. 34, no. 7. World Scientific Publishing, pp. 737–760, 2023.
ista: Ambrus Á, Csikós M, Kiss G, Pach J, Somlai G. 2023. Optimal embedded and enclosing
isosceles triangles. International Journal of Foundations of Computer Science.
34(7), 737–760.
mla: Ambrus, Áron, et al. “Optimal Embedded and Enclosing Isosceles Triangles.”
International Journal of Foundations of Computer Science, vol. 34, no.
7, World Scientific Publishing, 2023, pp. 737–60, doi:10.1142/S012905412342008X.
short: Á. Ambrus, M. Csikós, G. Kiss, J. Pach, G. Somlai, International Journal
of Foundations of Computer Science 34 (2023) 737–760.
date_created: 2023-10-29T23:01:18Z
date_published: 2023-10-05T00:00:00Z
date_updated: 2023-12-13T13:04:55Z
day: '05'
department:
- _id: HeEd
doi: 10.1142/S012905412342008X
external_id:
arxiv:
- '2205.11637'
isi:
- '001080874400001'
intvolume: ' 34'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2205.11637
month: '10'
oa: 1
oa_version: Preprint
page: 737-760
publication: International Journal of Foundations of Computer Science
publication_identifier:
eissn:
- 1793-6373
issn:
- 0129-0541
publication_status: published
publisher: World Scientific Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Optimal embedded and enclosing isosceles triangles
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2023'
...
---
_id: '14466'
abstract:
- lang: eng
text: The first long-lived turbulent structures observable in planar shear flows
take the form of localized stripes, inclined with respect to the mean flow direction.
The dynamics of these stripes is central to transition, and recent studies proposed
an analogy to directed percolation where the stripes’ proliferation is ultimately
responsible for the turbulence becoming sustained. In the present study we focus
on the internal stripe dynamics as well as on the eventual stripe expansion, and
we compare the underlying mechanisms in pressure- and shear-driven planar flows,
respectively, plane-Poiseuille and plane-Couette flow. Despite the similarities
of the overall laminar–turbulence patterns, the stripe proliferation processes
in the two cases are fundamentally different. Starting from the growth and sustenance
of individual stripes, we find that in plane-Couette flow new streaks are created
stochastically throughout the stripe whereas in plane-Poiseuille flow streak creation
is deterministic and occurs locally at the downstream tip. Because of the up/downstream
symmetry, Couette stripes, in contrast to Poiseuille stripes, have two weak and
two strong laminar turbulent interfaces. These differences in symmetry as well
as in internal growth give rise to two fundamentally different stripe splitting
mechanisms. In plane-Poiseuille flow splitting is connected to the elongational
growth of the original stripe, and it results from a break-off/shedding of the
stripe's tail. In plane-Couette flow splitting follows from a broadening of the
original stripe and a division along the stripe into two slimmer stripes.
acknowledgement: E.M. acknowledges funding from the ISTplus fellowship programme.
G.Y. and B.H. acknowledge a grant from the Simons Foundation (662960, BH).
article_number: A21
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Elena
full_name: Marensi, Elena
id: 0BE7553A-1004-11EA-B805-18983DDC885E
last_name: Marensi
orcid: 0000-0001-7173-4923
- first_name: Gökhan
full_name: Yalniz, Gökhan
id: 66E74FA2-D8BF-11E9-8249-8DE2E5697425
last_name: Yalniz
orcid: 0000-0002-8490-9312
- first_name: Björn
full_name: Hof, Björn
id: 3A374330-F248-11E8-B48F-1D18A9856A87
last_name: Hof
orcid: 0000-0003-2057-2754
citation:
ama: Marensi E, Yalniz G, Hof B. Dynamics and proliferation of turbulent stripes
in plane-Poiseuille and plane-Couette flows. Journal of Fluid Mechanics.
2023;974. doi:10.1017/jfm.2023.780
apa: Marensi, E., Yalniz, G., & Hof, B. (2023). Dynamics and proliferation of
turbulent stripes in plane-Poiseuille and plane-Couette flows. Journal of Fluid
Mechanics. Cambridge University Press. https://doi.org/10.1017/jfm.2023.780
chicago: Marensi, Elena, Gökhan Yalniz, and Björn Hof. “Dynamics and Proliferation
of Turbulent Stripes in Plane-Poiseuille and Plane-Couette Flows.” Journal
of Fluid Mechanics. Cambridge University Press, 2023. https://doi.org/10.1017/jfm.2023.780.
ieee: E. Marensi, G. Yalniz, and B. Hof, “Dynamics and proliferation of turbulent
stripes in plane-Poiseuille and plane-Couette flows,” Journal of Fluid Mechanics,
vol. 974. Cambridge University Press, 2023.
ista: Marensi E, Yalniz G, Hof B. 2023. Dynamics and proliferation of turbulent
stripes in plane-Poiseuille and plane-Couette flows. Journal of Fluid Mechanics.
974, A21.
mla: Marensi, Elena, et al. “Dynamics and Proliferation of Turbulent Stripes in
Plane-Poiseuille and Plane-Couette Flows.” Journal of Fluid Mechanics,
vol. 974, A21, Cambridge University Press, 2023, doi:10.1017/jfm.2023.780.
short: E. Marensi, G. Yalniz, B. Hof, Journal of Fluid Mechanics 974 (2023).
date_created: 2023-10-30T09:32:28Z
date_published: 2023-11-10T00:00:00Z
date_updated: 2024-02-15T09:06:23Z
day: '10'
ddc:
- '530'
department:
- _id: GradSch
- _id: BjHo
doi: 10.1017/jfm.2023.780
external_id:
arxiv:
- '2212.12406'
isi:
- '001088363700001'
file:
- access_level: open_access
checksum: 17c64c1fb0d5f73252364bf98b0b9e1a
content_type: application/pdf
creator: dernst
date_created: 2024-02-15T09:05:21Z
date_updated: 2024-02-15T09:05:21Z
file_id: '14996'
file_name: 2023_JourFluidMechanics_Marensi.pdf
file_size: 2804641
relation: main_file
success: 1
file_date_updated: 2024-02-15T09:05:21Z
has_accepted_license: '1'
intvolume: ' 974'
isi: 1
keyword:
- turbulence
- transition to turbulence
- patterns
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 238598C6-32DE-11EA-91FC-C7463DDC885E
grant_number: '662960'
name: 'Revisiting the Turbulence Problem Using Statistical Mechanics: Experimental
Studies on Transitional and Turbulent Flows'
publication: Journal of Fluid Mechanics
publication_identifier:
eissn:
- 1469-7645
issn:
- 0022-1120
publication_status: published
publisher: Cambridge University Press
quality_controlled: '1'
status: public
title: Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette
flows
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 974
year: '2023'
...
---
_id: '14472'
abstract:
- lang: eng
text: "Data related to the following paper:\r\n\"Stress granules plug and stabilize
damaged endolysosomal membranes\" (https://doi.org/10.1038/s41586-023-06726-w)\r\n\r\nAbstract:
\r\nEndomembrane damage represents a form of stress that is detrimental for eukaryotic
cells. To cope with this threat, cells possess mechanisms that repair the damage
and restore cellular homeostasis. Endomembrane damage also results in organelle
instability and the mechanisms by which cells stabilize damaged endomembranes
to enable membrane repair remains unknown. In this work we use a minimal coarse-grained
molecular dynamics system to explore how lipid vesicles undergoing poration in
a protein-rich medium can be plugged and stabilised by condensate formation. The
solution of proteins in and out of the vesicle is described by beads dispersed
in implicit solvent. The membrane is described as a one-bead-thick fluid elastic
layer of mechanical properties that mimic biological membranes. We tune the interactions
between solution beads in the different compartments to capture the differences
between the cytoplasmic and endosomal protein solutions and explore how the system
responds to different degrees of membrane poration. We find that, in the right
interaction regime, condensates form rapidly at the damage site upon solution
mixing and act as a plug that prevents futher mixing and destabilisation of the
vesicle. Further, when the condensate can interact with the membrane (wetting
interactions) we find that it mediates pore sealing and membrane repair. This
research is part of the work published in \"Stress granules plug and stabilize
damaged endolysosomal membranes\", Bussi et al, Nature, 2023 - 10.1038/s41586-023-06726-w."
article_processing_charge: No
author:
- first_name: Christian Eduardo
full_name: Vanhille-Campos, Christian Eduardo
id: 3adeca52-9313-11ed-b1ac-c170b2505714
last_name: Vanhille-Campos
- first_name: Anđela
full_name: Šarić, Anđela
id: bf63d406-f056-11eb-b41d-f263a6566d8b
last_name: Šarić
orcid: 0000-0002-7854-2139
citation:
ama: Vanhille-Campos CE, Šarić A. Stress granules plug and stabilize damaged endolysosomal
membranes. 2023. doi:10.15479/AT:ISTA:14472
apa: Vanhille-Campos, C. E., & Šarić, A. (2023). Stress granules plug and stabilize
damaged endolysosomal membranes. Institute of Science and Technology Austria.
https://doi.org/10.15479/AT:ISTA:14472
chicago: Vanhille-Campos, Christian Eduardo, and Anđela Šarić. “Stress Granules
Plug and Stabilize Damaged Endolysosomal Membranes.” Institute of Science and
Technology Austria, 2023. https://doi.org/10.15479/AT:ISTA:14472.
ieee: C. E. Vanhille-Campos and A. Šarić, “Stress granules plug and stabilize damaged
endolysosomal membranes.” Institute of Science and Technology Austria, 2023.
ista: Vanhille-Campos CE, Šarić A. 2023. Stress granules plug and stabilize damaged
endolysosomal membranes, Institute of Science and Technology Austria, 10.15479/AT:ISTA:14472.
mla: Vanhille-Campos, Christian Eduardo, and Anđela Šarić. Stress Granules Plug
and Stabilize Damaged Endolysosomal Membranes. Institute of Science and Technology
Austria, 2023, doi:10.15479/AT:ISTA:14472.
short: C.E. Vanhille-Campos, A. Šarić, (2023).
date_created: 2023-10-30T16:38:32Z
date_published: 2023-10-31T00:00:00Z
date_updated: 2023-11-27T09:05:07Z
day: '31'
ddc:
- '570'
department:
- _id: AnSa
doi: 10.15479/AT:ISTA:14472
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date_created: 2023-10-30T16:31:08Z
date_updated: 2023-10-30T16:31:08Z
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file_size: 62821432
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content_type: text/plain
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date_created: 2023-10-31T08:57:50Z
date_updated: 2023-10-31T08:57:50Z
file_id: '14474'
file_name: README.txt
file_size: 1697
relation: main_file
success: 1
file_date_updated: 2023-10-31T08:57:50Z
has_accepted_license: '1'
month: '10'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
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relation: used_in_publication
status: public
status: public
title: Stress granules plug and stabilize damaged endolysosomal membranes
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14478'
abstract:
- lang: eng
text: Entire chromosomes are typically only transmitted vertically from one generation
to the next. The horizontal transfer of such chromosomes has long been considered
improbable, yet gained recent support in several pathogenic fungi where it may
affect the fitness or host specificity. To date, it is unknown how these transfers
occur, how common they are and whether they can occur between different species.
In this study, we show multiple independent instances of horizontal transfers
of the same accessory chromosome between two distinct strains of the asexual entomopathogenic
fungusMetarhizium robertsiiduring experimental co-infection
of its insect host, the Argentine ant. Notably, only the one chromosome – but
no other – was transferred from the donor to the recipient strain. The recipient
strain, now harboring the accessory chromosome, exhibited a competitive advantage
under certain host conditions. By phylogenetic analysis we further demonstrate
that the same accessory chromosome was horizontally transferred in a natural environment
betweenM. robertsiiand another congeneric insect pathogen,M.
guizhouense. Hence horizontal chromosome transfer is not limited
to the observed frequent events within species during experimental infections
but also occurs naturally across species. The transferred accessory chromosome
contains genes that might be involved in its preferential horizontal transfer,
encoding putative histones and histone-modifying enzymes, but also putative virulence
factors that may support its establishment. Our study reveals that both intra-
and interspecies horizontal transfer of entire chromosomes is more frequent than
previously assumed, likely representing a not uncommon mechanism for gene exchange.Significance
StatementThe enormous success of bacterial pathogens has
been attributed to their ability to exchange genetic material between one another.
Similarly, in eukaryotes, horizontal transfer of genetic material allowed the
spread of virulence factors across species. The horizontal transfer of whole chromosomes
could be an important pathway for such exchange of genetic material, but little
is known about the origin of transferable chromosomes and how frequently they
are exchanged. Here, we show that the transfer of accessory chromosomes - chromosomes
that are non-essential but may provide fitness benefits - is common during fungal
co-infections and is even possible between distant pathogenic species, highlighting
the importance of horizontal gene transfer via chromosome transfer also for the
evolution and function of eukaryotic pathogens.
acknowledgement: We thank Bernhardt Steinwender, Jorgen Eilenberg and Nicolai V. Meyling
for the fungal strains. We further thank Chengshu Wang for providing the short sequencing
reads for M. guizhouense ARESF977 he used for his published genome assembly, and
Kristian Ullrich for help in the bioinformatics analysis for methylation pattern
in Nanopore reads, and the Vienna BioCenter and the Max Planck Society for the use
of their sequencing centers. We thank Barbara Milutinović and Hinrich Schulenburg
for discussion, and Tal Dagan and Jens Rolff for comments on a previous version
of the manuscript. Fig1 A was created with BioRender.com. This study received funding
by the European Research Council (ERC) under the European Union’s Horizon 2020 Research
and Innovation Programme (No. 771402; EPIDEMICSonCHIP) to S.C. and by the German
Research Foundation (DFG grant HA9263/1-1) to M.H.
article_processing_charge: No
author:
- first_name: Michael
full_name: Habig, Michael
last_name: Habig
- first_name: Anna V
full_name: Grasse, Anna V
id: 406F989C-F248-11E8-B48F-1D18A9856A87
last_name: Grasse
- first_name: Judith
full_name: Müller, Judith
last_name: Müller
- first_name: Eva H.
full_name: Stukenbrock, Eva H.
last_name: Stukenbrock
- first_name: Hanna
full_name: Leitner, Hanna
id: 8fc5c6f6-5903-11ec-abad-c83f046253e7
last_name: Leitner
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
citation:
ama: Habig M, Grasse AV, Müller J, Stukenbrock EH, Leitner H, Cremer S. Frequent
horizontal chromosome transfer between asexual fungal insect pathogens. bioRxiv.
doi:10.1101/2023.09.18.558174
apa: Habig, M., Grasse, A. V., Müller, J., Stukenbrock, E. H., Leitner, H., &
Cremer, S. (n.d.). Frequent horizontal chromosome transfer between asexual fungal
insect pathogens. bioRxiv. https://doi.org/10.1101/2023.09.18.558174
chicago: Habig, Michael, Anna V Grasse, Judith Müller, Eva H. Stukenbrock, Hanna
Leitner, and Sylvia Cremer. “Frequent Horizontal Chromosome Transfer between Asexual
Fungal Insect Pathogens.” BioRxiv, n.d. https://doi.org/10.1101/2023.09.18.558174.
ieee: M. Habig, A. V. Grasse, J. Müller, E. H. Stukenbrock, H. Leitner, and S. Cremer,
“Frequent horizontal chromosome transfer between asexual fungal insect pathogens,”
bioRxiv. .
ista: Habig M, Grasse AV, Müller J, Stukenbrock EH, Leitner H, Cremer S. Frequent
horizontal chromosome transfer between asexual fungal insect pathogens. bioRxiv,
10.1101/2023.09.18.558174.
mla: Habig, Michael, et al. “Frequent Horizontal Chromosome Transfer between Asexual
Fungal Insect Pathogens.” BioRxiv, doi:10.1101/2023.09.18.558174.
short: M. Habig, A.V. Grasse, J. Müller, E.H. Stukenbrock, H. Leitner, S. Cremer,
BioRxiv (n.d.).
date_created: 2023-10-31T13:30:00Z
date_published: 2023-09-19T00:00:00Z
date_updated: 2023-11-07T11:20:54Z
day: '19'
department:
- _id: SyCr
doi: 10.1101/2023.09.18.558174
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2023.09.18.558174
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 2649B4DE-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '771402'
name: Epidemics in ant societies on a chip
publication: bioRxiv
publication_status: submitted
status: public
title: Frequent horizontal chromosome transfer between asexual fungal insect pathogens
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...