Lacoste-Julien, Simon

86 publications

ICLR 2025 Accelerating Training with Neuron Interaction and Nowcasting Networks Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien

AISTATS 2025 Feasible Learning Juan Ramirez, Ignacio Hounie, Juan Elenter, Jose Gallego-Posada, Meraj Hashemizadeh, Alejandro Ribeiro, Simon Lacoste-Julien

AISTATS 2025 Performative Prediction on Games and Mechanism Design António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien

ICLRW 2025 Performative Prediction on Games and Mechanism Design António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien

NeurIPS 2025 Tight Lower Bounds and Improved Convergence in Performative Prediction Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel

NeurIPS 2025 Understanding Adam Requires Better Rotation Dependent Assumptions Tianyue H. Zhang, Lucas Maes, Alan Milligan, Alexia Jolicoeur-Martineau, Ioannis Mitliagkas, Damien Scieur, Simon Lacoste-Julien, Charles Guille-Escuret

ICLR 2024 Balancing Act: Constraining Disparate Impact in Sparse Models Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada

ICML 2024 On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization Motahareh Sohrabi, Juan Ramirez, Tianyue H. Zhang, Simon Lacoste-Julien, Jose Gallego-Posada

ICMLW 2024 On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization Motahareh Sohrabi, Juan Ramirez, Tianyue H. Zhang, Simon Lacoste-Julien, Jose Gallego-Posada

CLeaR 2024 On the Identifiability of Quantized Factors Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICMLW 2024 Performative Prediction on Games and Mechanism Design António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Simon Lacoste-Julien, Gauthier Gidel

TMLR 2024 PopulAtion Parameter Averaging (PAPA) Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien

TMLR 2024 Promoting Exploration in Memory-Augmented Adam Using Critical Momenta Pranshu Malviya, Goncalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar

NeurIPSW 2024 Tight Lower Bounds and Improved Convergence in Performative Prediction Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel

NeurIPSW 2024 Understanding Adam Requires Better Rotation Dependent Assumptions Tianyue H. Zhang, Lucas Maes, Alexia Jolicoeur-Martineau, Ioannis Mitliagkas, Damien Scieur, Simon Lacoste-Julien, Charles Guille-Escuret

AISTATS 2024 Weight-Sharing Regularization Mehran Shakerinava, Motahareh MS Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien

NeurIPS 2023 Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien

ICML 2023 Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? Boris Knyazev, Doha Hwang, Simon Lacoste-Julien

ICML 2023 CrossSplit: Mitigating Label Noise Memorization Through Data Splitting Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICML 2023 Synergies Between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sebastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand

ICML 2023 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

AISTATS 2022 On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng, Sebastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang

UAI 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio

ICLRW 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Chinenye Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio

NeurIPS 2022 Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien

NeurIPS 2022 Data-Efficient Structured Pruning via Submodular Optimization Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien

CLeaR 2022 Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sebastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien

NeurIPS 2022 Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou

ICLR 2022 Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

ICLR 2022 Online Adversarial Attacks Andjela Mladenovic, Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

MLJ 2022 SVRG Meets AdaGrad: Painless Variance Reduction Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien

NeurIPSW 2022 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

NeurIPSW 2022 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

AISTATS 2021 An Analysis of the Adaptation Speed of Causal Models Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien

AISTATS 2021 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

AISTATS 2021 Stochastic Polyak Step-Size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien

ICML 2021 Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur

ICLR 2021 Repurposing Pretrained Models for Robust Out-of-Domain Few-Shot Learning Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien

NeurIPS 2021 Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis Under Expected Co-Coercivity Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien

ICML 2021 Structured Convolutional Kernel Networks for Airline Crew Scheduling Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien

ICLR 2020 A Closer Look at the Optimization Landscapes of Generative Adversarial Networks Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

AISTATS 2020 A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel

AISTATS 2020 Accelerating Smooth Games by Manipulating Spectral Shapes Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel

NeurIPS 2020 Adversarial Example Games Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, Will Hamilton

NeurIPS 2020 Differentiable Causal Discovery from Interventional Data Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

AISTATS 2020 Fast and Furious Convergence: Stochastic Second Order Methods Under Interpolation Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji), Mark Schmidt, Simon Lacoste-Julien

AISTATS 2020 GAIT: A Geometric Approach to Information Theory Jose Gallego Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien

ICLR 2020 Gradient-Based Neural DAG Learning Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien

NeurIPSW 2020 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

ICMLW 2019 A Modern Take on the Bias-Variance Tradeoff in Neural Networks Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas

ICLR 2019 A Variational Inequality Perspective on Generative Adversarial Networks Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

NeurIPSW 2019 Gradient-Based Neural DAG Learning Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien

NeurIPS 2019 Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks Gauthier Gidel, Francis Bach, Simon Lacoste-Julien

AISTATS 2019 Negative Momentum for Improved Game Dynamics Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas

NeurIPS 2019 Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani, Aaron Mishkin, Issam Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

NeurIPS 2019 Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien

UAI 2018 Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien

AISTATS 2018 Frank-Wolfe Splitting via Augmented Lagrangian Method Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien

JMLR 2018 Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods Remi Leblond, Fabian Pedregosa, Simon Lacoste-Julien

NeurIPS 2018 Quantifying Learning Guarantees for Convex but Inconsistent Surrogates Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin

ICLR 2018 SEARNN: Training RNNs with Global-Local Losses Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien

ICML 2017 A Closer Look at Memorization in Deep Networks Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien

AISTATS 2017 ASAGA: Asynchronous Parallel SAGA Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien

NeurIPS 2017 Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien

AISTATS 2017 Frank-Wolfe Algorithms for Saddle Point Problems Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien

ICCV 2017 Joint Discovery of Object States and Manipulation Actions Jean-Baptiste Alayrac, Ivan Laptev, Josef Sivic, Simon Lacoste-Julien

NeurIPS 2017 On Structured Prediction Theory with Calibrated Convex Surrogate Losses Anton Osokin, Francis Bach, Simon Lacoste-Julien

ICML 2016 Beyond CCA: Moment Matching for Multi-View Models Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien

ICML 2016 Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Dokania, Simon Lacoste-Julien

NeurIPS 2016 PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain, Francis Bach, Alexandre Lacoste, Simon Lacoste-Julien

CVPR 2016 Unsupervised Learning from Narrated Instruction Videos Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien

NeurIPS 2015 Barrier Frank-Wolfe for Marginal Inference Rahul G Krishnan, Simon Lacoste-Julien, David Sontag

CVPR 2015 On Pairwise Costs for Network Flow Multi-Object Tracking Visesh Chari, Simon Lacoste-Julien, Ivan Laptev, Josef Sivic

NeurIPS 2015 On the Global Linear Convergence of Frank-Wolfe Optimization Variants Simon Lacoste-Julien, Martin Jaggi

NeurIPS 2015 Rethinking LDA: Moment Matching for Discrete ICA Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien

AISTATS 2015 Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach

NeurIPS 2015 Variance Reduced Stochastic Gradient Descent with Neighbors Thomas Hofmann, Aurelien Lucchi, Simon Lacoste-Julien, Brian McWilliams

NeurIPS 2014 SAGA: A Fast Incremental Gradient Method with Support for Non-Strongly Convex Composite Objectives Aaron Defazio, Francis Bach, Simon Lacoste-Julien

ICML 2013 Block-Coordinate Frank-Wolfe Optimization for Structural SVMs Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher

ICML 2012 On the Equivalence Between Herding and Conditional Gradient Algorithms Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski

NeurIPS 2008 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification Simon Lacoste-Julien, Fei Sha, Michael I. Jordan

JMLR 2006 Structured Prediction, Dual Extragradient and Bregman Projections Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan

NeurIPS 2005 Structured Prediction via the Extragradient Method Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan