Simon Lacoste-Julien

173 papers A* 35A 19Journal 101Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation. CoRR Vitória Barin Pacela, Shruti Joshi, Isabela Camacho, Simon Lacoste-Julien, David A. Klindt
2025	A*	`conf`	Accelerating Training with Neuron Interaction and Nowcasting Networks. ICLR Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien
2025	J	`jnl`	Bias Analysis in Unconditional Image Generative Models. CoRR Xiaofeng Zhang, Michelle P. Lin, Simon Lacoste-Julien, Aaron C. Courville, Yash Goyal
2025	J	`jnl`	Cooper: A Library for Constrained Optimization in Deep Learning. CoRR Jose Gallego-Posada, Juan Ramirez, Meraj Hashemizadeh, Simon Lacoste-Julien
2025	J	`jnl`	Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise. CoRR Juan Ramirez, Simon Lacoste-Julien
2025	A	`conf`	Feasible Learning. AISTATS Juan Ramirez, Ignacio Hounie, Juan Elenter, Jose Gallego-Posada, Meraj Hashemizadeh, Alejandro Ribeiro, Simon Lacoste-Julien
2025	J	`jnl`	Feasible Learning. CoRR Juan Ramirez, Ignacio Hounie, Juan Elenter, Jose Gallego-Posada, Meraj Hashemizadeh, Alejandro Ribeiro, Simon Lacoste-Julien
2025	A*	`ed.`	Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025 ICML Aarti Singh, Maryam Fazel, Daniel Hsu, Simon Lacoste-Julien, Felix Berkenkamp, Tegan Maharaj, Kiri Wagstaff, Jerry Zhu
2025	J	`jnl`	Operationalizing Quantized Disentanglement. CoRR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2025	A	`conf`	Performative Prediction on Games and Mechanism Design. AISTATS António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien
2025	J	`jnl`	Position: Adopt Constraints Over Penalties in Deep Learning. CoRR Juan Ramirez, Meraj Hashemizadeh, Simon Lacoste-Julien
2024	J	`jnl`	Accelerating Training with Neuron Interaction and Nowcasting Networks. CoRR Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien
2024	A*	`conf`	Balancing Act: Constraining Disparate Impact in Sparse Models. ICLR Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada
2024	J	`jnl`	Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2024	A*	`conf`	On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization. ICML Motahareh Sohrabi, Juan Ramirez, Tianyue H. Zhang, Simon Lacoste-Julien, Jose Gallego-Posada
2024	J	`jnl`	On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization. CoRR Motahareh Sohrabi, Juan Ramirez, Tianyue H. Zhang, Simon Lacoste-Julien, Jose Gallego-Posada
2024	—	`conf`	On the Identifiability of Quantized Factors. CLeaR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2024	J	`jnl`	Performative Prediction on Games and Mechanism Design. CoRR António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Simon Lacoste-Julien, Gauthier Gidel
2024	J	`jnl`	PopulAtion Parameter Averaging (PAPA). Trans. Mach. Learn. Res. Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien
2024	J	`jnl`	Promoting Exploration in Memory-Augmented Adam using Critical Momenta. Trans. Mach. Learn. Res. Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
2024	J	`jnl`	Tight Lower Bounds and Improved Convergence in Performative Prediction. CoRR Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel
2024	J	`jnl`	Understanding Adam Requires Better Rotation Dependent Assumptions. CoRR Lucas Maes, Tianyue H. Zhang, Alexia Jolicoeur-Martineau, Ioannis Mitliagkas, Damien Scieur, Simon Lacoste-Julien, Charles Guille-Escuret
2024	A	`conf`	Weight-Sharing Regularization. AISTATS Mehran Shakerinava, Motahareh Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien
2023	J	`jnl`	A Survey of Self-Supervised and Few-Shot Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez
2023	A*	`conf`	Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. NeurIPS Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
2023	J	`jnl`	Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. CoRR Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
2023	J	`jnl`	Balancing Act: Constraining Disparate Impact in Sparse Models. CoRR Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada
2023	A*	`conf`	Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? ICML Boris Knyazev, Doha Hwang, Simon Lacoste-Julien
2023	J	`jnl`	Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? CoRR Boris Knyazev, Doha Hwang, Simon Lacoste-Julien
2023	A*	`conf`	CrossSplit: Mitigating Label Noise Memorization through Data Splitting. ICML Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
2023	J	`jnl`	Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection. CoRR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2023	J	`jnl`	PopulAtion Parameter Averaging (PAPA). CoRR Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien
2023	J	`jnl`	Promoting Exploration in Memory-Augmented Adam using Critical Momenta. CoRR Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
2023	A*	`conf`	Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
2023	A*	`conf`	Unlocking Slot Attention by Changing Optimal Transport Costs. ICML Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
2023	J	`jnl`	Unlocking Slot Attention by Changing Optimal Transport Costs. CoRR Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
2023	J	`jnl`	Weight-Sharing Regularization. CoRR Mehran Shakerinava, Motahareh Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien
2022	J	`jnl`	Bayesian Structure Learning with Generative Flow Networks. CoRR Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
2022	A	`conf`	Bayesian structure learning with generative flow networks. UAI Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
2022	A*	`conf`	Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. NeurIPS Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
2022	J	`jnl`	Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. CoRR Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
2022	J	`jnl`	CrossSplit: Mitigating Label Noise Memorization through Data Splitting. CoRR Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
2022	A*	`conf`	Data-Efficient Structured Pruning via Submodular Optimization. NeurIPS Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
2022	J	`jnl`	Data-Efficient Structured Pruning via Submodular Optimization. CoRR Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
2022	—	`conf`	Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2022	A*	`conf`	Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution. NeurIPS Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou
2022	A*	`conf`	Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. ICLR Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
2022	A	`conf`	On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
2022	A*	`conf`	Online Adversarial Attacks. ICLR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2022	J	`jnl`	Partial Disentanglement via Mechanism Sparsity. CoRR Sébastien Lachapelle, Simon Lacoste-Julien
2022	J	`jnl`	Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS J. Comput. Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi
2022	J	`jnl`	SVRG meets AdaGrad: painless variance reduction. Mach. Learn. Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien
2022	J	`jnl`	Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
2021	J	`jnl`	A Survey of Self-Supervised and Few-Shot Object Detection. CoRR Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez
2021	A*	`conf`	Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets. ICML Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur
2021	A	`conf`	An Analysis of the Adaptation Speed of Causal Models. AISTATS Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien
2021	J	`jnl`	Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent - an Open Problem. CoRR Rémi Le Priol, Frederik Kunstner, Damien Scieur, Simon Lacoste-Julien
2021	J	`jnl`	Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2021	A	`conf`	Implicit Regularization via Neural Feature Alignment. AISTATS Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2021	J	`jnl`	Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. CoRR Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
2021	J	`jnl`	Online Adversarial Attacks. CoRR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2021	A*	`conf`	Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning. ICLR Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
2021	J	`jnl`	Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning. CoRR Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
2021	J	`jnl`	SVRG Meets AdaGrad: Painless Variance Reduction. CoRR Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien
2021	A*	`conf`	Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. NeurIPS Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
2021	J	`jnl`	Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. CoRR Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
2021	A	`conf`	Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. AISTATS Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien
2021	A*	`conf`	Structured Convolutional Kernel Networks for Airline Crew Scheduling. ICML Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
2021	J	`jnl`	Structured Convolutional Kernel Networks for Airline Crew Scheduling. CoRR Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
2020	A*	`conf`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2020	A	`conf`	A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games. AISTATS Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	A	`conf`	Accelerating Smooth Games by Manipulating Spectral Shapes. AISTATS Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	J	`jnl`	Accelerating Smooth Games by Manipulating Spectral Shapes. CoRR Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	J	`jnl`	Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search). CoRR Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien
2020	A*	`conf`	Adversarial Example Games. NeurIPS Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	J	`jnl`	Adversarial Example Games. CoRR Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	J	`jnl`	An Analysis of the Adaptation Speed of Causal Models. CoRR Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio, Simon Lacoste-Julien
2020	A*	`conf`	Differentiable Causal Discovery from Interventional Data. NeurIPS Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	J	`jnl`	Differentiable Causal Discovery from Interventional Data. CoRR Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	A	`conf`	Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. AISTATS Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien
2020	J	`jnl`	Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer. CoRR Yassine Yaakoubi, Simon Lacoste-Julien, François Soumis
2020	A	`conf`	GAIT: A Geometric Approach to Information Theory. AISTATS Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
2020	J	`jnl`	Geometry-Aware Universal Mirror-Prox. CoRR Reza Babanezhad, Simon Lacoste-Julien
2020	A*	`conf`	Gradient-Based Neural DAG Learning. ICLR Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
2020	J	`jnl`	Implicit Regularization in Deep Learning: A View from Function Space. CoRR Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2020	J	`jnl`	Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation. CoRR Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
2020	J	`jnl`	Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation. EURO J. Transp. Logist. Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
2020	J	`jnl`	On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
2020	A*	`conf`	Stochastic Hamiltonian Gradient Methods for Smooth Games. ICML Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
2020	J	`jnl`	Stochastic Hamiltonian Gradient Methods for Smooth Games. CoRR Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
2020	J	`jnl`	Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. CoRR Nicolas Loizou, Sharan Vaswani, Issam H. Laradji, Simon Lacoste-Julien
2020	J	`jnl`	To Each Optimizer a Norm, To Each Norm its Generalization. CoRR Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux
2019	J	`jnl`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2019	J	`jnl`	A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games. CoRR Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2019	—	`conf`	A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien
2019	J	`jnl`	Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification. CoRR Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien
2019	J	`jnl`	Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. CoRR Si Yi Meng, Sharan Vaswani, Issam H. Laradji, Mark Schmidt, Simon Lacoste-Julien
2019	J	`jnl`	GEAR: Geometry-Aware Rényi Information. CoRR Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
2019	J	`jnl`	Gradient-Based Neural DAG Learning. CoRR Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
2019	J	`jnl`	Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks. CoRR Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
2019	A*	`conf`	Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks. NeurIPS Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
2019	A	`conf`	Negative Momentum for Improved Game Dynamics. AISTATS Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas
2019	A*	`conf`	Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
2019	J	`jnl`	Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
2019	A*	`conf`	Reducing Noise in GAN Training with Variance Reduced Extragradient. NeurIPS Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
2019	J	`jnl`	Reducing Noise in GAN Training with Variance Reduced Extragradient. CoRR Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
2019	J	`jnl`	Scattering Networks for Hybrid Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
2018	J	`jnl`	A Modern Take on the Bias-Variance Tradeoff in Neural Networks. CoRR Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas
2018	J	`jnl`	A Variational Inequality Perspective on Generative Adversarial Nets. CoRR Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien
2018	J	`jnl`	A3T: Adversarially Augmented Adversarial Training. CoRR Akram Erraqabi, Aristide Baratin, Yoshua Bengio, Simon Lacoste-Julien
2018	A	`conf`	Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields. UAI Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien
2018	A	`conf`	Frank-Wolfe Splitting via Augmented Lagrangian Method. AISTATS Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods. J. Mach. Learn. Res. Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Improved asynchronous parallel optimization analysis for stochastic incremental methods. CoRR Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Learning from Narrated Instruction Videos. IEEE Trans. Pattern Anal. Mach. Intell. Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
2018	J	`jnl`	Negative Momentum for Improved Game Dynamics. CoRR Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien, Ioannis Mitliagkas
2018	—	`conf`	Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien
2018	J	`jnl`	Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning. CoRR Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi
2018	A*	`conf`	Quantifying Learning Guarantees for Convex but Inconsistent Surrogates. NeurIPS Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
2018	J	`jnl`	Quantifying Learning Guarantees for Convex but Inconsistent Surrogates. CoRR Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
2018	—	`conf`	SEARNN: Training RNNs with global-local losses. ICLR (Poster) Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien
2018	J	`jnl`	Scattering Networks for Hybrid Representation Learning. CoRR Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
2017	A*	`conf`	A Closer Look at Memorization in Deep Networks. ICML Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien
2017	J	`jnl`	A Closer Look at Memorization in Deep Networks. CoRR Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien
2017	A	`conf`	ASAGA: Asynchronous Parallel SAGA. AISTATS Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2017	J	`jnl`	Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields. CoRR Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien
2017	J	`jnl`	Adversarial Divergences are Good Task Losses for Generative Modeling. CoRR Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien
2017	—	`conf`	Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. NIPS Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
2017	J	`jnl`	Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. CoRR Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
2017	A	`conf`	Frank-Wolfe Algorithms for Saddle Point Problems. AISTATS Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
2017	J	`jnl`	Joint Discovery of Object States and Manipulating Actions. CoRR Jean-Baptiste Alayrac, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
2017	A*	`conf`	Joint Discovery of Object States and Manipulation Actions. ICCV Jean-Baptiste Alayrac, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
2017	—	`conf`	On Structured Prediction Theory with Calibrated Convex Surrogate Losses. NIPS Anton Osokin, Francis R. Bach, Simon Lacoste-Julien
2017	J	`jnl`	On Structured Prediction Theory with Calibrated Convex Surrogate Losses. CoRR Anton Osokin, Francis R. Bach, Simon Lacoste-Julien
2017	J	`jnl`	SEARNN: Training RNNs with Global-Local Losses. CoRR Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien
2016	J	`jnl`	Asaga: Asynchronous Parallel Saga. CoRR Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2016	A*	`conf`	Beyond CCA: Moment Matching for Multi-View Models. ICML Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien
2016	J	`jnl`	Beyond CCA: Moment Matching for Multi-View Models. CoRR Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien
2016	J	`jnl`	Convergence Rate of Frank-Wolfe for Non-Convex Objectives. CoRR Simon Lacoste-Julien
2016	J	`jnl`	Frank-Wolfe Algorithms for Saddle Point Problems. CoRR Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
2016	A*	`conf`	Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs. ICML Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Kumar Dokania, Simon Lacoste-Julien
2016	J	`jnl`	Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs. CoRR Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Kumar Dokania, Simon Lacoste-Julien
2016	—	`conf`	PAC-Bayesian Theory Meets Bayesian Inference. NIPS Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien
2016	J	`jnl`	PAC-Bayesian Theory Meets Bayesian Inference. CoRR Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien
2016	A*	`conf`	Unsupervised Learning from Narrated Instruction Videos. CVPR Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
2015	—	`conf`	Barrier Frank-Wolfe for Marginal Inference. NIPS Rahul G. Krishnan, Simon Lacoste-Julien, David A. Sontag
2015	J	`jnl`	Barrier Frank-Wolfe for Marginal Inference. CoRR Rahul G. Krishnan, Simon Lacoste-Julien, David A. Sontag
2015	J	`jnl`	Learning from narrated instruction videos. CoRR Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, Simon Lacoste-Julien
2015	A*	`conf`	On pairwise costs for network flow multi-object tracking. CVPR Visesh Chari, Simon Lacoste-Julien, Ivan Laptev, Josef Sivic
2015	—	`conf`	On the Global Linear Convergence of Frank-Wolfe Optimization Variants. NIPS Simon Lacoste-Julien, Martin Jaggi
2015	J	`jnl`	On the Global Linear Convergence of Frank-Wolfe Optimization Variants. CoRR Simon Lacoste-Julien, Martin Jaggi
2015	—	`conf`	Rethinking LDA: Moment Matching for Discrete ICA. NIPS Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien
2015	J	`jnl`	Rethinking LDA: moment matching for discrete ICA. CoRR Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien
2015	A	`conf`	Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. AISTATS Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach
2015	J	`jnl`	Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. CoRR Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach
2015	—	`conf`	Variance Reduced Stochastic Gradient Descent with Neighbors. NIPS Thomas Hofmann, Aurélien Lucchi, Simon Lacoste-Julien, Brian McWilliams
2014	J	`jnl`	On Pairwise Cost for Multi-Object Network Flow Tracking. CoRR Visesh Chari, Simon Lacoste-Julien, Ivan Laptev, Josef Sivic
2014	—	`conf`	SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. NIPS Aaron Defazio, Francis R. Bach, Simon Lacoste-Julien
2014	J	`jnl`	SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. CoRR Aaron Defazio, Francis R. Bach, Simon Lacoste-Julien
2013	—	`conf`	Block-Coordinate Frank-Wolfe Optimization for Structural SVMs. ICML (1) Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher
2013	A*	`conf`	SIGMa: simple greedy matching for aligning large knowledge bases. KDD Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
2012	J	`jnl`	A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method CoRR Simon Lacoste-Julien, Mark Schmidt, Francis R. Bach
2012	J	`jnl`	On the Equivalence between Herding and Conditional Gradient Algorithms CoRR Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski
2012	A*	`conf`	On the Equivalence between Herding and Conditional Gradient Algorithms. ICML Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski
2012	J	`jnl`	SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases CoRR Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
2012	J	`jnl`	Stochastic Block-Coordinate Frank-Wolfe Optimization for Structural SVMs CoRR Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher
2011	A	`conf`	Approximate inference for the loss-calibrated Bayesian. AISTATS Simon Lacoste-Julien, Ferenc Huszar, Zoubin Ghahramani
2008	—	`conf`	DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification. NIPS Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
2006	J	`jnl`	Structured Prediction, Dual Extragradient and Bregman Projections. J. Mach. Learn. Res. Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan
2006	—	`conf`	Word Alignment via Quadratic Assignment. HLT-NAACL Simon Lacoste-Julien, Benjamin Taskar, Dan Klein, Michael I. Jordan
2005	—	`conf`	A Discriminative Matching Approach to Word Alignment. HLT/EMNLP Benjamin Taskar, Simon Lacoste-Julien, Dan Klein
2005	—	`conf`	Structured Prediction via the Extragradient Method. NIPS Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan