David Balduzzi

Real World Games Look Like Spinning Tops

Apr 20, 2020
Wojciech Marian Czarnecki, Gauthier Gidel, Brendan Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg

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Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games

Feb 27, 2020
Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach

* Accepted for publication at AAMAS 2020

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From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

Feb 19, 2020
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls

* 43 pages

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Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets

Feb 14, 2020
Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki, Marta Garnelo, Yoram Bachrach

* 15 pages

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Smooth markets: A basic mechanism for organizing gradient-based learners

Jan 18, 2020
David Balduzzi, Wojciech M Czarnecki, Thomas W Anthony, Ian M Gemp, Edward Hughes, Joel Z Leibo, Georgios Piliouras, Thore Graepel

* ICLR 2020
* 18 pages, 3 figures

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LOGAN: Latent Optimisation for Generative Adversarial Networks

Dec 02, 2019
Yan Wu, Jeff Donahue, David Balduzzi, Karen Simonyan, Timothy Lillicrap

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Differentiable Game Mechanics

May 13, 2019
Alistair Letcher, David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

* Journal of Machine Learning Research (JMLR), v20 (84) 1-40, 2019
* JMLR 2019, journal version of arXiv:1802.05642

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Open-ended Learning in Symmetric Zero-sum Games

Jan 23, 2019
David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech M. Czarnecki, Julien Perolat, Max Jaderberg, Thore Graepel

* 18 pages, 7 figures

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Stable Opponent Shaping in Differentiable Games

Nov 20, 2018
Alistair Letcher, Jakob Foerster, David Balduzzi, Tim Rocktäschel, Shimon Whiteson

* 20 pages, 7 figures

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Re-evaluating Evaluation

Oct 30, 2018
David Balduzzi, Karl Tuyls, Julien Perolat, Thore Graepel

* NIPS 2018, final version

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The Mechanics of n-Player Differentiable Games

Jun 06, 2018
David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

* PMLR volume 80, 2018
* ICML 2018, final version

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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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Strongly-Typed Agents are Guaranteed to Interact Safely

Jun 06, 2018
David Balduzzi

* 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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Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation

Aug 01, 2016
Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, Wen Li

* to appear in European Conference on Computer Vision (ECCV) 2016

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Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization

Jul 26, 2016
Muhammad Ghifary, David Balduzzi, W. Bastiaan Kleijn, Mengjie Zhang

* to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence

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Strongly-Typed Recurrent Neural Networks

May 24, 2016
David Balduzzi, Muhammad Ghifary

* 10 pages, final version, ICML 2016

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Deep Online Convex Optimization by Putting Forecaster to Sleep

Apr 08, 2016
David Balduzzi

* Rendered obsolete by arXiv:1604.01952. The new version contains the same basic results, with major changes to exposition and minor changes to terminology

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Deep Online Convex Optimization with Gated Games

Apr 07, 2016
David Balduzzi

* 13 pages. This paper renders arXiv:1509.01851 obsolete. It contains the same basic results, with major changes to exposition and minor changes to terminology

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