Simon Lacoste-Julien

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Gauthier GidelAssistant professor at Mila, University of Montréal (DIRO)Verified email at umontreal.ca
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Mark SchmidtAssociate Professor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Pascal VincentFacebook AI Research; U. Montreal (Professor, Computer Sc. & Op. Res.); MILA; CIFARVerified email at iro.umontreal.ca
Hugo BerardPhD student, MILA, University of MontrealVerified email at umontreal.ca
Ioannis (Yannis) MitliagkasAssociate Professor at Mila, University of MontréalVerified email at iro.umontreal.ca
Gabriel HuangPhD candidate, Mila & Visiting Researcher, ServiceNowVerified email at umontreal.ca
Sébastien LachapellePhD Student, Mila, Université de MontréalVerified email at umontreal.ca
Martin JaggiEPFLVerified email at epfl.ch
Ben TaskarUniversity of WashingtonVerified email at cs.washington.edu
Sharan VaswaniSimon Fraser UniversityVerified email at sfu.ca
Josef SivicCzech Technical University, CIIRC, ELLIS Unit PragueVerified email at cvut.cz
Ivan LaptevResearch director, INRIAVerified email at inria.fr
Jean-Baptiste AlayracDeepMind, LondonVerified email at google.com
Issam H. LaradjiSenior Research Scientist at ServiceNow & Adjunct Professor at University of BritishVerified email at servicenow.com
Rémi Le PriolPhD from MILA, University of MontréalVerified email at umontreal.ca
Aaron DefazioFundamental AI Research team, Meta NYVerified email at anu.edu.au
Aristide BaratinResearch scientist, Samsung - SAIT AI Lab MontrealVerified email at mila.quebec

Simon Lacoste-Julien

Associate Professor - Canada CIFAR AI Chair, University of Montreal / Mila

Verified email at iro.umontreal.ca - Homepage

Machine Learning Statistics Optimization


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SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives A Defazio, F Bach, S Lacoste-Julien NIPS 2014 - Advances in Neural Information Processing Systems 27, 1646-1654, 2014	1824	2014
A Closer Look at Memorization in Deep Networks D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... ICML 2017 - Proceedings of the 34th International Conference on Machine Learning, 2017	1373	2017
DiscLDA: Discriminative learning for dimensionality reduction and classification S Lacoste-Julien, F Sha, MI Jordan NIPS 2008 - Advances in Neural Information Processing Systems 21, 2008	529	2008
Block-Coordinate Frank-Wolfe Optimization for Structural SVMs S Lacoste-Julien, M Jaggi, M Schmidt, P Pletscher ICML 2013 - Proceedings of the 30th International Conference on Machine …, 2013	423	2013
On the Global Linear Convergence of Frank-Wolfe Optimization Variants S Lacoste-Julien, M Jaggi NIPS 2015 - Advances in Neural Information Processing Systems 28, 2015	418	2015
A Variational Inequality Perspective on Generative Adversarial Nets G Gidel, H Berard, G Vignoud, P Vincent, S Lacoste-Julien ICLR 2019 - Seventh International Conference on Learning Representations, 2019	335*	2019
Unsupervised Learning from Narrated Instruction Videos JB Alayrac, P Bojanowski, N Agrawal, J Sivic, I Laptev, S Lacoste-Julien CVPR 2016 - Proceedings of the IEEE Conference on Computer Vision and …, 2016	303	2016
A discriminative matching approach to word alignment B Taskar, S Lacoste-Julien, D Klein EMNLP 2005 - Proceedings of the conference on Human Language Technology and …, 2005	256	2005
A Simpler Approach to Obtaining an O(1/t) Convergence Rate for the Projected Stochastic Subgradient Method S Lacoste-Julien, M Schmidt, F Bach arXiv preprint arXiv:1212.2002, 2012	241	2012
Convergence Rate of Frank-Wolfe for Non-Convex Objectives S Lacoste-Julien arXiv preprint arXiv:1607.00345, 2016	188	2016
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases S Lacoste-Julien, K Palla, A Davies, G Kasneci, T Graepel, Z Ghahramani KDD 2013 - Proceedings of the 19th ACM SIGKDD international conference on …, 2013	188	2013
On Pairwise Costs for Network Flow Multi-Object Tracking V Chari, S Lacoste-Julien, I Laptev, J Sivic CVPR 2015 - Proceedings of the IEEE Conference on Computer Vision and …, 2015	167	2015
On the Equivalence between Herding and Conditional Gradient Algorithms F Bach, S Lacoste-Julien, G Obozinski ICML 2012 - Proceedings of the 29th International Conference on Machine Learning, 2012	165	2012
Negative Momentum for Improved Game Dynamics G Gidel, R Askari, M Pezeshki, R Le Priol, G Huang, S Lacoste-Julien, ... AISTATS 2019 - Proceedings of the 22nd International Conference on …, 2019	163	2019
PAC-Bayesian Theory Meets Bayesian Inference P Germain, F Bach, A Lacoste, S Lacoste-Julien NIPS 2016 - Advances in Neural Information Processing Systems 29, 2016	157	2016
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates S Vaswani, A Mishkin, I Laradji, M Schmidt, G Gidel, S Lacoste-Julien NeurIPS 2019 - Advances in Neural Information Processing Systems 32, 2019	154	2019
A Modern Take on the Bias-Variance Tradeoff in Neural Networks B Neal, S Mittal, A Baratin, V Tantia, M Scicluna, S Lacoste-Julien, ... arXiv preprint arXiv:1810.08591, 2018	153	2018
Gradient-Based Neural DAG Learning S Lachapelle, P Brouillard, T Deleu, S Lacoste-Julien ICLR 2020 - Eight International Conference on Learning Representations, 2020	149	2020
Variance Reduced Stochastic Gradient Descent with Neighbors T Hofmann, A Lucchi, S Lacoste-Julien, B McWilliams NIPS 2015 - Advances in Neural Information Processing Systems 28, 2015	148	2015
Structured prediction, dual extragradient and Bregman projections B Taskar, S Lacoste-Julien, MI Jordan JMLR - Journal of Machine Learning Research 7, 1627-1653, 2006	145	2006

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