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October 2026 A Surrogate Perspective on Convergence of Fixed-Target DQN accepted at NeurIPS 2026.
October 2026 I am recruiting PhD and MSc students for Fall 2027. See how to apply .
May 2026 Hiroki Naganuma has completed his PhD and joins NVIDIA. Congratulations Dr. Naganuma!
May 2026 Two papers accepted at ICML 2026, on unlearning with public data and on adaptive batch sizes for sign and spectral descent .
January 2026 Three papers accepted at ICLR 2026, including Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries .
September 2025 Understanding Adam Requires Better Rotation Dependent Assumptions accepted at NeurIPS 2025.
May 2025 Compositional Risk Minimization accepted at ICML 2025.
January 2025 Charles Guille-Escuret has completed his PhD and joins the MBZUAI Institute of Foundation Models. Congratulations Dr. Guille-Escuret!
June 2024 One more strong PhD graduation, this time it is Adam Ibrahim! He continues his work as a research scientist at H, Paris. Congratulations Dr. Ibrahim!
May 2024 No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths paper accepted at ICML 2024!
May 2024 For the first time in a long while, I'm attending a big ML conference. I will be at ICLR 2024 in Vienna.
April 2024 My second PhD student to graduate, Reyhane Askari Hemmat, has successfully defended her thesis. She continues her work as a research scientist at Meta, Montreal. Congratulations Dr. Askari!
January 2024 Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation paper accepted at ICLR 2024 for an spotlight presentation.
January 2024 LEAD: Min-Max Optimization from a Physical Perspective invited to be presented at ICLR 2024
December 2023 For the winter semester of 2024, I am on sabbatical at Archimedes in Athens, Greece.
September 2023 Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation paper accepted at NeurIPS 2023 for an oral presentation
September 2023 CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning paper accepted at NeurIPS 2023
September 2023 Welcome to new PhD student, Zichu Liu .
September 2023 Welcome to new intern, Ange-Clement Akazan who's visitting us from the African Institute for Mathematical Research and will study generative models
April 2023 Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning paper accepted at ICML 2023.
January 2023 My first PhD student to graduate, Alexia Jolicoeur-Martineau, has successfully defended her thesis. She continues her work as a research scientist at SAIL Montreal. Congratulations Dr. Jolicoeur-Martineau!!
January 2023 Performative Prediction with Neural Networks paper accepted at AISTASTS 2023.
January 2023 Neural Networks Efficiently Learn Low-Dimensional Representations with SGD paper accepted at ICLR 2023 with honorable mention.
September 2022 I'm excited to announce that I've started part-time work as a staff research scientist at Google Brain Montreal! Looking forward to deepening my connection to larger scale problems in industry.
September 2022 Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound paper accepted at NeurIPS 2022.
September 2022 Kartik Ahuja has finished his postdoc and started working as a research scientist at Meta research (FAIR) Paris!
July 2022 Graduating PhD candidate Alexia Jolicoeur-Martineau started work at Samsung SAIT AI Lab in Montreal!
June 2022 As of June 1st, 2022 I was promoted to the post of associate professor with tenure. My sincere thanks to colleagues and my group for all their hard work.
October 2021 Honored to be invited to the semester of Learning and Games at Simons. I will be visitting Berkeley in January-March of 2022.
September 2021 Welcome to new MSc students, Mehrnaz Mofakhami and Divyat Mahajan .
September 2021 Two papers accepted at NeurIPS 2021! [one , two ]
April 2021 Postdoc in our group, Nicolas Loizou accepted a tenure track position at Johns Hopkins University!
March 2021 Postdoc in our group, Manuela Girotti accepted a tenure track position at St. Mary's University! In the meantime shewill spend time at the prestigious mathematical institute, MSRI, in Berkeley, CA.
January 2021 Best student paper award for Charles, Baptiste and Manuela's paper at OPT2020! For their work on the fundamentals of condition numbers . Their paper was accepted for publication at AISTATS 2021.
January 2021 Alexia and Rémi's paper, in collaboration with MSR Montréal has been accepted at ICLR 2021! Preprint available here .
September 2020 Paper on evaluating generalization measures accepted at NeurIPS'20.
September 2020 Welcome to new PhD students, Ryan D'Orazio and Hiroki Naganuma .
August 2020 Kartik Ahuja awarded the IVADO postdoctoral scholarship. Excited to have him join us in January 2021!
April 2020 Two papers on differentiable games (one , two ) accepted at ICML'20.
January 2020 Two papers on efficient methods and tight bounds for differentiable games (one , two ) accepted at AISTATS'20.
December 2019 Nicolas Loizou was awarded the IVADO postdoctoral scholarship at the prestigious Fellow tier.
December 2019 Brady Neal graduates with an MSc. He will continue on his PhD with us.
November 2019 Excited to be coorganizing the 2nd iteration of the Smooth Games Optimization and Machine Learning Workshop at NeurIPS'19.
November 2019 Reducing the variance in online optimization by transporting past gradients selected for spotlight oral presentation at NeurIPS'19.
October 2019 Multiple submissions to AISTATS. Preprints on the way...
June 2019 At ICML with 3 papers in main conference, 2 in Deep Learning Phenomena workshop.
May 2019 State-Reification Networks selected for oral presentation at ICML'19.
April 2019 Excited to be listed among the most prolific authors of accepted ICML 2019 papers.
April 2019 I received the NSERC Discovery grant!
April 2019 In Japan for AISTATS.
January 2019 h-detach paper accepted at ICLR.
December 2018 Was nominated in the first cohort of Canada CIFAR AI chairs!!
December 2018 Co-organizing Smooth Games Optimization in ML workshop at NeurIPS.
December 2018 Negative momentum for improved game dynamics. Paper accepted at AISTATS 2019.
December 2018 Full version of YellowFin manscript accepted at SysML
September 2018 Excited to be teaching Machine Learning to a class of 180 graduate students at UdeM.
February 2018 YellowFin selected for oral presentation at SysML'18.
January 2018 Teaching new class! IFT 6085: Theoretical principles for deep learning
December 2017 Accelerated power iteration via momentum, paper accepted at AISTATS 2018.
November 2017 Talk at Google Brain, Montréal
September 2017 Thrilled to be starting work at the University of Montreal and the Mila as an assistant professor!
August 2017 Visiting my alma mater, UT Austin.
August 2017 At Sydney for ICML, presenting work on YellowFin, custom scans for Gibbs sampling, and deep learning for 3D point cloud representation and generation.
July 2017 New preprint! Representation Learning and Adversarial Generation of 3D Point Clouds [arxiv] .
July 2017 New preprint! Accelerated stochastic power iteration [arxiv] .
June 2017 New preprint! An automatic tuner for they hyperparameters of momentum SGD [arxiv] .
May 2017 Custom scan sequence paper accepted for presentation at ICML 2017!
April 2017 Invited talk at Workshop on Advances in Computing Architectures, Stanford SystemX
March 2017 New preprint! Custom scan sequences for super fast Gibbs sampling .
February 2017 Invited to talk at ITA in San Diego.
February 2017 Spoke at the AAAI 2017 Workshop on Distributed Machine Learning.
January 2017 Visiting Microsoft Research, Cambridge
December 2016 At NIPS, presenting our Gibbs sampling paper dispelling some common beliefs regarding scan orders.
November 2016 Visiting Microsoft Research New England
November 2016 Invited talk at SystemX Stanford Alliance Fall Conference
November 2016 Full version of asynchrony paper .
September 2016 Talk at Allerton
August 2016 I had the pleasure to give a talk MIT Lincoln Labs.
August 2016 Gave an asynchronous optimization talk at Google.
August 2016 Blog post on our momentum work.
July 2016 Invited to talk at NVIDIA.
June 2016 Poster at non-convex optimization ICML workshop .
June 2016 Poster at OptML 2016 workshop.
2016 In a recent note , we show that asynchrony in SGD introduces momentum. In the companion systems paper , we use this theory to train deep networks faster.
2016 Does periodic model averaging always help? Recent results .
2015 Excited to start Postdoc at Stanford University. Will be working with Lester Mackey and Chris Ré.
2015 Successfully defended my PhD thesis!
2015 SILO seminar talk at the Wisconsin Institute of Discovery.
2015 Densest k-Subgraph work picked up by NVIDIA !
2015 Our latest work has been accepted for presentation at VLDB 2015!