McWilliams, Brian

17 publications

ICML 2024 MusicRL: Aligning Music Generation to Human Preferences Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zalán Borsos, Brian Mcwilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Leonard Hussenot, Neil Zeghidour, Andrea Agostinelli

ICLR 2023 The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium Ian Gemp, Charlie Chen, Brian McWilliams

ICLR 2022 EigenGame Unloaded: When Playing Games Is Better than Optimizing Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

ICLRW 2022 EigenGame Unloaded: When Playing Games Is Better than Optimizing Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

ICMLW 2022 Pushing the Limits of Self-Supervised ResNets: Can We Outperform Supervised Learning Without Labels on ImageNet? Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

ICLR 2021 EigenGame: PCA as a Nash Equilibrium Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

ICLR 2021 Representation Learning via Invariant Causal Mechanisms Jovana Mitrovic, Brian McWilliams, Jacob C Walker, Lars Holger Buesing, Charles Blundell

NeurIPSW 2020 Less Can Be More in Contrastive Learning Jovana Mitrovic, Brian McWilliams, Melanie Rey

CVPRW 2018 A Fully Progressive Approach to Single-Image Super-Resolution Yifan Wang, Federico Perazzi, Brian McWilliams, Alexander Sorkine-Hornung, Olga Sorkine-Hornung, Christopher Schroers

ICML 2017 Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks David Balduzzi, Brian McWilliams, Tony Butler-Yeoman

ICML 2017 The Shattered Gradients Problem: If Resnets Are the Answer, Then What Is the Question? David Balduzzi, Marcus Frean, Lennox Leary, J. P. Lewis, Kurt Wan-Duo Ma, Brian McWilliams

CVPR 2016 A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, Alexander Sorkine-Hornung

AISTATS 2016 DUAL-LOCO: Distributing Statistical Estimation Using Random Projections Christina Heinze, Brian McWilliams, Nicolai Meinshausen

NeurIPS 2016 Scalable Adaptive Stochastic Optimization Using Random Projections Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M Buhmann, Nicolai Meinshausen

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

NeurIPS 2014 Fast and Robust Least Squares Estimation in Corrupted Linear Models Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M Buhmann

NeurIPS 2013 Correlated Random Features for Fast Semi-Supervised Learning Brian McWilliams, David Balduzzi, Joachim M Buhmann