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Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning


Mar 16, 2021
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien

* Appears in: Proceedings of the Ninth International Conference on Learning Representations (ICLR 2021). 20 pages 

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Online Adversarial Attacks


Mar 02, 2021
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

* Preprint 

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SVRG Meets AdaGrad: Painless Variance Reduction


Feb 18, 2021
Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien


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On the Convergence of Continuous Constrained Optimization for Structure Learning


Dec 16, 2020
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien

* NeurIPS 2020 Workshop on Causal Discovery and Causality-Inspired Machine Learning 

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Geometry-Aware Universal Mirror-Prox


Nov 23, 2020
Reza Babanezhad, Simon Lacoste-Julien


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Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation


Sep 30, 2020
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien

* EURO Journal on Transportation and Logistics, 100020 (2020) 
* First publication in the "Cahiers du GERAD" series in February 2020. Submitted to EURO Journal on Transportation and Logistics on January 17, 2020 and available online on September 2, 2020 

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Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer


Sep 26, 2020
Yassine Yaakoubi, Simon Lacoste-Julien, François Soumis

* First publication on the "Cahiers du GERAD" series in April 2019 

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Implicit Regularization in Deep Learning: A View from Function Space


Aug 03, 2020
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

* 24 pages. A preliminary version of this work has been presented at the NeurIPS 2019 Workshops on "Machine Learning with Guarantees" and "Science meets Engineering of Deep Learning" 

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Stochastic Hamiltonian Gradient Methods for Smooth Games


Jul 08, 2020
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

* ICML 2020 - Proceedings of the 37th International Conference on Machine Learning 

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Differentiable Causal Discovery from Interventional Data


Jul 03, 2020
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

* 34 pages 

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Adversarial Example Games


Jul 01, 2020
Avishek Joey Bose, Gauthier Gidel, Hugo Berrard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton


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Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search)


Jun 11, 2020
Sharan Vaswani, Frederik Kunstner, Issam Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien


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To Each Optimizer a Norm, To Each Norm its Generalization


Jun 11, 2020
Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux


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An Analysis of the Adaptation Speed of Causal Models


May 18, 2020
Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio, Simon Lacoste-Julien

* 22 pages, 8 figures 

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Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence


Feb 24, 2020
Nicolas Loizou, Sharan Vaswani, Issam Laradji, Simon Lacoste-Julien

* 27 pages, 5 figures 

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Accelerating Smooth Games by Manipulating Spectral Shapes


Jan 02, 2020
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel


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Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation


Oct 11, 2019
Si Yi Meng, Sharan Vaswani, Issam Laradji, Mark Schmidt, Simon Lacoste-Julien


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A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games


Jun 24, 2019
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel


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GEAR: Geometry-Aware Rényi Information


Jun 19, 2019
Jose Gallego, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien


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A Closer Look at the Optimization Landscapes of Generative Adversarial Networks


Jun 11, 2019
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien


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Gradient-Based Neural DAG Learning


Jun 05, 2019
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien

* 15 pages 

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Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates


May 24, 2019
Sharan Vaswani, Aaron Mishkin, Issam Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien


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Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks


Apr 30, 2019
Gauthier Gidel, Francis Bach, Simon Lacoste-Julien

* 25 pages 

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Reducing Noise in GAN Training with Variance Reduced Extragradient


Apr 18, 2019
Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien


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Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification


Feb 22, 2019
Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien


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Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information


Jan 22, 2019
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi

* arXiv admin note: substantial text overlap with arXiv:1807.11876 

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A Variational Inequality Perspective on Generative Adversarial Networks


Nov 02, 2018
Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

* 33 pages 

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Quantifying Learning Guarantees for Convex but Inconsistent Surrogates


Oct 26, 2018
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin

* Appears in: Advances in Neural Information Processing Systems 31 (NIPS 2018). 18 pages 

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