Simon Lacoste-Julien

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 130

Top Venues

Publications

Motahareh Sohrabi, Juan Ramirez, Tianyue H. Zhang, Simon Lacoste-Julien, Jose Gallego-Posada
On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization. CoRR (2024)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. Trans. Mach. Learn. Res. 2024 (2024)
Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien
PopulAtion Parameter Averaging (PAPA). Trans. Mach. Learn. Res. 2024 (2024)
Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR (2024)
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada
Balancing Act: Constraining Disparate Impact in Sparse Models. ICLR (2024)
Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
On the Identifiability of Quantized Factors. CLeaR (2024)
Mehran Shakerinava, Motahareh Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien
Weight-Sharing Regularization. AISTATS (2024)
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Unlocking Slot Attention by Changing Optimal Transport Costs. ICML (2023)
Boris Knyazev, Doha Hwang, Simon Lacoste-Julien
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? CoRR (2023)
Boris Knyazev, Doha Hwang, Simon Lacoste-Julien
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? ICML (2023)
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada
Balancing Act: Constraining Disparate Impact in Sparse Models. CoRR (2023)
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Unlocking Slot Attention by Changing Optimal Transport Costs. CoRR (2023)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. CoRR (2023)
Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. CoRR (2023)
Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. ICML (2023)
Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. NeurIPS (2023)
Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection. CoRR (2023)
Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez
A Survey of Self-Supervised and Few-Shot Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 45 (4) (2023)
Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien
PopulAtion Parameter Averaging (PAPA). CoRR (2023)
Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML (2023)
Mehran Shakerinava, Motahareh Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien
Weight-Sharing Regularization. CoRR (2023)
Sébastien Lachapelle, Simon Lacoste-Julien
Partial Disentanglement via Mechanism Sparsity. CoRR (2022)
Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. NeurIPS (2022)
Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR (2022)
Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien
SVRG meets AdaGrad: painless variance reduction. Mach. Learn. 111 (12) (2022)
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi
Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS J. Comput. 34 (1) (2022)
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
Online Adversarial Attacks. ICLR (2022)
Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution. NeurIPS (2022)
Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. CoRR (2022)
Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR (2022)
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. ICLR (2022)
Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
Data-Efficient Structured Pruning via Submodular Optimization. NeurIPS (2022)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS (2022)
Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. CoRR (2022)
Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
Bayesian Structure Learning with Generative Flow Networks. CoRR (2022)
Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
Bayesian structure learning with generative flow networks. UAI (2022)
Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
Data-Efficient Structured Pruning via Submodular Optimization. CoRR (2022)
Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR (2021)
Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. NeurIPS (2021)
Rémi Le Priol, Frederik Kunstner, Damien Scieur, Simon Lacoste-Julien
Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent - an Open Problem. CoRR (2021)
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning. CoRR (2021)
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
Structured Convolutional Kernel Networks for Airline Crew Scheduling. ICML (2021)
Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien
SVRG Meets AdaGrad: Painless Variance Reduction. CoRR (2021)
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
Online Adversarial Attacks. CoRR (2021)
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets. ICML (2021)
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. CoRR (2021)
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning. ICLR (2021)
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
Structured Convolutional Kernel Networks for Airline Crew Scheduling. CoRR (2021)
Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. CoRR (2021)
Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien
An Analysis of the Adaptation Speed of Causal Models. AISTATS (2021)
Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. AISTATS (2021)
Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez
A Survey of Self-Supervised and Few-Shot Object Detection. CoRR (2021)
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
Implicit Regularization via Neural Feature Alignment. AISTATS (2021)
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
Stochastic Hamiltonian Gradient Methods for Smooth Games. ICML (2020)
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
Implicit Regularization in Deep Learning: A View from Function Space. CoRR (2020)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. NeurIPS (2020)
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
Accelerating Smooth Games by Manipulating Spectral Shapes. AISTATS (2020)
Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. AISTATS (2020)
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR (2020)
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
Gradient-Based Neural DAG Learning. ICLR (2020)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. CoRR (2020)
Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
GAIT: A Geometric Approach to Information Theory. AISTATS (2020)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR (2020)
Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux
To Each Optimizer a Norm, To Each Norm its Generalization. CoRR (2020)
Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio, Simon Lacoste-Julien
An Analysis of the Adaptation Speed of Causal Models. CoRR (2020)
Nicolas Loizou, Sharan Vaswani, Issam H. Laradji, Simon Lacoste-Julien
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. CoRR (2020)
Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
Adversarial Example Games. NeurIPS (2020)
Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien
Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search). CoRR (2020)
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
Stochastic Hamiltonian Gradient Methods for Smooth Games. CoRR (2020)
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation. CoRR (2020)
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games. AISTATS (2020)
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
Accelerating Smooth Games by Manipulating Spectral Shapes. CoRR (2020)
Yassine Yaakoubi, Simon Lacoste-Julien, François Soumis
Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer. CoRR (2020)
Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
Adversarial Example Games. CoRR (2020)
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation. EURO J. Transp. Logist. 9 (4) (2020)
Reza Babanezhad, Simon Lacoste-Julien
Geometry-Aware Universal Mirror-Prox. CoRR (2020)
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas
Negative Momentum for Improved Game Dynamics. AISTATS (2019)
Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks. NeurIPS (2019)
Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
GEAR: Geometry-Aware Rényi Information. CoRR (2019)
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
Gradient-Based Neural DAG Learning. CoRR (2019)
Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS (2019)
Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien
Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification. CoRR (2019)
Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien
A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) (2019)
Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
Reducing Noise in GAN Training with Variance Reduced Extragradient. NeurIPS (2019)
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games. CoRR (2019)
Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks. CoRR (2019)
Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR (2019)
Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
Reducing Noise in GAN Training with Variance Reduced Extragradient. CoRR (2019)
Si Yi Meng, Sharan Vaswani, Issam H. Laradji, Mark Schmidt, Simon Lacoste-Julien
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. CoRR (2019)
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
Scattering Networks for Hybrid Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. 41 (9) (2019)
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR (2019)
Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
Learning from Narrated Instruction Videos. IEEE Trans. Pattern Anal. Mach. Intell. 40 (9) (2018)
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien, Ioannis Mitliagkas
Negative Momentum for Improved Game Dynamics. CoRR (2018)
Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR (2018)
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates. CoRR (2018)
Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) (2018)
Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien
Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields. UAI (2018)
Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas
A Modern Take on the Bias-Variance Tradeoff in Neural Networks. CoRR (2018)
Akram Erraqabi, Aristide Baratin, Yoshua Bengio, Simon Lacoste-Julien
A3T: Adversarially Augmented Adversarial Training. CoRR (2018)
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates. NeurIPS (2018)

Simon Lacoste-Julien.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Simon Lacoste-Julien