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Unsupervised Object-based Transition Models For Embodied Agents in 3D Partially Observable Environments.

Antonia Creswell, Rishabh Kabra, Chris Burgess, Murray Shanahan

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An Empirical Investigation of Learning from Biased Toxicity Labels

Neel Nanda *, Sven Gowal, Jonathan Uesato

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Neural rate control for video encoding using imitation learning

Hongzi Mao *, Chenjie Gu, Miaosen Wang, Nir Levine, Nevena Lazic, Derek Pang *, Rene Claus *, Angie Chiang *, C Chen *, Jingning Han *, Marisabel Hechtman *, A Chen *

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Ponder Net

Andrea Banino, Jan Balaguer, Charles Blundell

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Revisiting Peng's Q(λ) for modern reinforcement learning

Tadashi Kozuno *, Yunhao Tang *, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel

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Taylor expansions of discount factors

Yunhao Tang *, Remi Munos, Mark Rowland, Michal Valko

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Kernel-based reinforcement Learning: A finite-time analysis

O Domingues *, Pierre Menard *, Matteo Pirotta *, Emilie Kaufmann *, Michal Valko

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Counterfactual Credit Assignment

Thomas Mesnard, Theophane Weber, Fabio Viola, Alaa Saade, Shantanu Thakoor, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Éric Moulines *, Arthur Guez, Marcus Hutter, Lars Buesing, Remi Munos

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Online A-optimal design and active linear regression

Xavier Fontaine *, Pierre Perrault *, Michal Valko, V Perchet *

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PsiPhi: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning

Angelos Filos, Clare Lyle *, Yarin Gal *, Sergey Levine *, Natasha Jaques *, Greg Farquhar

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Fast active learning for pure exploration in reinforcement learning

Pierre Ménard *, O Domingues *, Emilie Kaufmann *, Anders Jonsson *, Edouard Leurent *, Michal Valko

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Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers

Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel

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Bad-Policy Density: A Measure of Reinforcement Learning Hardness

David Abel, Cameron Allen *, Dilip Arumugam *, D. Ellis Hershkowitz *, Michael Littman *, Lawson. L.S. Wong *

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Reasoning-Modulated Representations

Petar Veličković, Matko Bošnjak, Thomas Kipf *, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell

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CoBERL: Contrastive BERT for Reinforcement Learning

Andrea Banino, Adrià Puigdomènech, Jacob Walker, Tim Scholtes, Jovana Mitrović, Charles Blundell

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Imitation by Predicting Observations

Drew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Gregory Wayne

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Emphatic Algorithms for Deep Reinforcement Learning

Ray Jiang, Tom Zahavy, Adam White, Zhongwen Xu, Matteo Hessel, Charles Blundell, Hado van Hasselt

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A Closer Look at the Adversarial Robustness of Information Bottleneck Models

Iryna Korshunova *, Sven Gowal, Alex Alemi *, Olivia Wiles, David Stutz

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Vector Quantized Models for Planning

Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals

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A Distribution-Dependent Analysis of Meta-Learning

Mikhail Konobeev *, Ilja Kuzborskij, Csaba Szepesvari

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Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games

Dustin Morrill *, Ryan D'Orazio *, Marc Lanctot, Reca Sarfati *, James Wright *, Amy Greenwald *, Michael Bowling

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Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation

Xu Han *, X Chen *, J Hu *, Francisco Ruiz, Liping Liu *

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Robust Learning-Augmented Caching: An Experimental Study

Jakub Chledowski *, Adam Polak *, Bartosz Szabucki *, Konrad Zolna

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Leveraging Non-uniformity in First-order Non-convex Optimization

Jincheng Mei *, Yue Gao *, Bo Dai *, Csaba Szepesvari, Dale Schuurmans *

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Spectral normalisation for Deep Reinforcement Learning: an Optimisation Perspective

Florin Gogianu *, Tudor Berariu *, Mihaela Rosca, Claudia Clopath *, Razvan Pascanu, Claudia Clopath

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