Simon Lacoste-Julien 个人学术档案

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引用	12279	9334
h 指数	48	43
i10 指数	79	74

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Gauthier GidelAssistant professor at Mila, University of Montréal (DIRO)在 umontreal.ca 的电子邮件经过验证
Francis BachInria - Ecole Normale Supérieure在 inria.fr 的电子邮件经过验证
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFAR在 umontreal.ca 的电子邮件经过验证
Pascal VincentFacebook AI Research; U. Montreal (Professor, Computer Sc. & Op. Res.); MILA; CIFAR在 iro.umontreal.ca 的电子邮件经过验证
Sébastien LachapellePhD Student, Mila, Université de Montréal在 umontreal.ca 的电子邮件经过验证
Mark SchmidtAssociate Professor of Computer Science, University of British Columbia在 cs.ubc.ca 的电子邮件经过验证
Hugo BerardPhD student, MILA, University of Montreal在 umontreal.ca 的电子邮件经过验证
Ioannis (Yannis) MitliagkasAssociate Professor at Mila, University of Montréal在 iro.umontreal.ca 的电子邮件经过验证
Gabriel HuangPhD candidate, Mila & Visiting Researcher, ServiceNow在 umontreal.ca 的电子邮件经过验证
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
Sharan VaswaniSimon Fraser University在 sfu.ca 的电子邮件经过验证
Martin JaggiEPFL在 epfl.ch 的电子邮件经过验证
Rémi Le PriolPhD from MILA, University of Montréal在 umontreal.ca 的电子邮件经过验证
Issam H. LaradjiStaff Research Scientist at ServiceNow & Adjunct Professor at University of British Columbia在 servicenow.com 的电子邮件经过验证
Josef SivicCzech Technical University, CIIRC, ELLIS Unit Prague在 cvut.cz 的电子邮件经过验证
Ivan LaptevVisiting professor at MBZUAI, on leave from INRIA在 inria.fr 的电子邮件经过验证
Jean-Baptiste AlayracDeepMind, London在 google.com 的电子邮件经过验证
Ben TaskarUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Alexandre LacosteStaff Research Scientist, ServiceNow Research在 servicenow.com 的电子邮件经过验证
Aristide BaratinResearch scientist, Samsung - SAIT AI Lab Montreal在 mila.quebec 的电子邮件经过验证

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Simon Lacoste-Julien

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

在 iro.umontreal.ca 的电子邮件经过验证 - 首页

Machine Learning Statistics Optimization


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	2110	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	1914	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	541	2008
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	466	2015
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	442	2013
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	427*	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	353	2016
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	279	2012
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	258	2005
Gradient-Based Neural DAG Learning S Lachapelle, P Brouillard, T Deleu, S Lacoste-Julien ICLR 2020 - Eight International Conference on Learning Representations, 2020	239	2020
Convergence Rate of Frank-Wolfe for Non-Convex Objectives S Lacoste-Julien arXiv preprint arXiv:1607.00345, 2016	227	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	213	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	210	2018
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	201	2013
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	198	2016
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	192	2019
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	177	2012
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	172	2015
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	170	2015
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence N Loizou, S Vaswani, I Laradji, S Lacoste-Julien AISTATS 2021 - arXiv preprint arXiv:2002.10542, 2021	164	2021

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