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EigenGame Unloaded: When playing games is better than optimizing


Feb 08, 2021
Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel


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Representation Learning via Invariant Causal Mechanisms


Oct 15, 2020
Jovana Mitrovic, Brian McWilliams, Jacob Walker, Lars Buesing, Charles Blundell


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EigenGame: PCA as a Nash Equilibrium


Oct 01, 2020
Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel


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Social diversity and social preferences in mixed-motive reinforcement learning


Feb 12, 2020
Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo

* Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020) 

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Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning


Feb 06, 2020
Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo


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Spectrogram Feature Losses for Music Source Separation


Jan 18, 2019
Abhimanyu Sahai, Romann Weber, Brian McWilliams

* provided greater details on model parameters (result unchanged); small correction in plot legend 

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Neural Importance Sampling


Sep 27, 2018
Thomas Müller, Brian McWilliams, Fabrice Rousselle, Markus Gross, Jan Novák

* 16 pages, 12 figures. Submitted to ACM Trans. Graph 

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Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks


Jun 06, 2018
David Balduzzi, Brian McWilliams, Tony Butler-Yeoman

* PMLR volume 70, 2017 
* ICML 2017, final version 

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The Shattered Gradients Problem: If resnets are the answer, then what is the question?


Jun 06, 2018
David Balduzzi, Marcus Frean, Lennox Leary, JP Lewis, Kurt Wan-Duo Ma, Brian McWilliams

* PMLR volume 70 (2017) 
* ICML 2017, final version 

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A Fully Progressive Approach to Single-Image Super-Resolution


Apr 10, 2018
Yifan Wang, Federico Perazzi, Brian McWilliams, Alexander Sorkine-Hornung, Olga Sorkine-Hornung, Christopher Schroers


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PhaseNet for Video Frame Interpolation


Apr 03, 2018
Simone Meyer, Abdelaziz Djelouah, Brian McWilliams, Alexander Sorkine-Hornung, Markus Gross, Christopher Schroers

* CVPR 2018 

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Deep Scattering: Rendering Atmospheric Clouds with Radiance-Predicting Neural Networks


Sep 15, 2017
Simon Kallweit, Thomas Müller, Brian McWilliams, Markus Gross, Jan Novák

* ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2017) 

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Preserving Differential Privacy Between Features in Distributed Estimation


Jun 27, 2017
Christina Heinze-Deml, Brian McWilliams, Nicolai Meinshausen

* Stat 7 (1), 2018 

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Scalable Adaptive Stochastic Optimization Using Random Projections


Nov 21, 2016
Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen

* To appear in Advances in Neural Information Processing Systems 29 (NIPS 2016) 

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Variance Reduced Stochastic Gradient Descent with Neighbors


Feb 26, 2016
Thomas Hofmann, Aurelien Lucchi, Simon Lacoste-Julien, Brian McWilliams

* Appears in: Advances in Neural Information Processing Systems 28 (NIPS 2015). 13 pages 

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DUAL-LOCO: Distributing Statistical Estimation Using Random Projections


Jan 08, 2016
Christina Heinze, Brian McWilliams, Nicolai Meinshausen

* Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 51, 2016, 12 pages 
* 13 pages 

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Learning Representations for Outlier Detection on a Budget


Jul 29, 2015
Barbora Micenková, Brian McWilliams, Ira Assent


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A Variance Reduced Stochastic Newton Method


Jun 09, 2015
Aurelien Lucchi, Brian McWilliams, Thomas Hofmann


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LOCO: Distributing Ridge Regression with Random Projections


Jun 08, 2015
Christina Heinze, Brian McWilliams, Nicolai Meinshausen, Gabriel Krummenacher

* 37 pages 

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Fast and Robust Least Squares Estimation in Corrupted Linear Models


Jun 19, 2014
Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann


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Correlated random features for fast semi-supervised learning


Nov 05, 2013
Brian McWilliams, David Balduzzi, Joachim M. Buhmann

* 15 pages, 3 figures, 6 tables 

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Subspace clustering of high-dimensional data: a predictive approach


Mar 05, 2012
Brian McWilliams, Giovanni Montana


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Multi-view predictive partitioning in high dimensions


Feb 02, 2012
Brian McWilliams, Giovanni Montana

* 31 pages, 12 figures 

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Sparse partial least squares for on-line variable selection in multivariate data streams


Feb 08, 2009
Brian McWilliams, Giovanni Montana

* 26 pages, 6 figures, submitted 

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