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A Combinatorial Perspective on Transfer Learning

Oct 23, 2020
Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness


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Gaussian Gated Linear Networks

Jun 10, 2020
David Budden, Adam Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness


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Online Learning in Contextual Bandits using Gated Linear Networks

Feb 21, 2020
Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness


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Task-Relevant Adversarial Imitation Learning

Oct 02, 2019
Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gomez Colmenarej, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang


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Gated Linear Networks

Sep 30, 2019
Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter

* arXiv admin note: substantial text overlap with arXiv:1712.01897 

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A Framework for Data-Driven Robotics

Sep 26, 2019
Serkan Cabi, Sergio G贸mez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott Reed, Rae Jeong, Konrad 呕o艂na, Yusuf Aytar, David Budden, Mel Vecerik, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang


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Modular Meta-Learning with Shrinkage

Sep 12, 2019
Yutian Chen, Abram L. Friesen, Feryal Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas

* 14 pages (4 main, 8 supplement), under review 

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A Generalized Framework for Population Based Training

Feb 05, 2019
Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta

* 9 pages 

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TF-Replicator: Distributed Machine Learning for Researchers

Feb 01, 2019
Peter Buchlovsky, David Budden, Dominik Grewe, Chris Jones, John Aslanides, Frederic Besse, Andy Brock, Aidan Clark, Sergio G贸mez Colmenarejo, Aedan Pope, Fabio Viola, Dan Belov


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One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL

Oct 11, 2018
Tom Le Paine, Sergio G贸mez Colmenarejo, Ziyu Wang, Scott Reed, Yusuf Aytar, Tobias Pfaff, Matt W. Hoffman, Gabriel Barth-Maron, Serkan Cabi, David Budden, Nando de Freitas


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Sample Efficient Adaptive Text-to-Speech

Sep 27, 2018
Yutian Chen, Yannis Assael, Brendan Shillingford, David Budden, Scott Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Caglar Gulcehre, A盲ron van den Oord, Oriol Vinyals, Nando de Freitas


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Observe and Look Further: Achieving Consistent Performance on Atari

May 29, 2018
Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, Gabriel Barth-Maron, Hado van Hasselt, John Quan, Mel Ve膷er铆k, Matteo Hessel, R茅mi Munos, Olivier Pietquin


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Playing hard exploration games by watching YouTube

May 29, 2018
Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas


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Distributed Distributional Deterministic Policy Gradients

Apr 23, 2018
Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy Lillicrap


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Distributed Prioritized Experience Replay

Mar 02, 2018
Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver

* Accepted to International Conference on Learning Representations 2018 

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DeepMind Control Suite

Jan 02, 2018
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, Martin Riedmiller

* 24 pages, 7 figures, 2 tables 

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Deep Tensor Convolution on Multicores

Jun 11, 2017
David Budden, Alexander Matveev, Shibani Santurkar, Shraman Ray Chaudhuri, Nir Shavit

* 11 pages, 4 figures, 1 supplementary doc 

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Generative Compression

Jun 04, 2017
Shibani Santurkar, David Budden, Nir Shavit


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Toward Streaming Synapse Detection with Compositional ConvNets

Feb 23, 2017
Shibani Santurkar, David Budden, Alexander Matveev, Heather Berlin, Hayk Saribekyan, Yaron Meirovitch, Nir Shavit

* 10 pages, 9 figures 

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A Multi-Pass Approach to Large-Scale Connectomics

Dec 07, 2016
Yaron Meirovitch, Alexander Matveev, Hayk Saribekyan, David Budden, David Rolnick, Gergely Odor, Seymour Knowles-Barley, Thouis Raymond Jones, Hanspeter Pfister, Jeff William Lichtman, Nir Shavit

* 18 pages, 10 figures 

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Addressing the non-functional requirements of computer vision systems: A case study

Oct 31, 2014
Shannon Fenn, Alexandre Mendes, David Budden

* 17 pages, 4 figures 

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Simulation leagues: Analysis of competition formats

Jun 26, 2014
David Budden, Peter Wang, Oliver Obst, Mikhail Prokopenko

* 12 pages, 2 figures, presented at RoboCup 2014 symposium, Brazil 

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RANSAC: Identification of Higher-Order Geometric Features and Applications in Humanoid Robot Soccer

Oct 22, 2013
Madison Flannery, Shannon Fenn, David Budden

* 8 pages, 6 figures 

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