Search Results for author: Ben Coppin

Found 5 papers, 1 papers with code

Statistical discrimination in learning agents

no code implementations21 Oct 2021 Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo

Undesired bias afflicts both human and algorithmic decision making, and may be especially prevalent when information processing trade-offs incentivize the use of heuristics.

Decision Making Multi-agent Reinforcement Learning

Large-Scale Visual Speech Recognition

no code implementations ICLR 2019 Brendan Shillingford, Yannis Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Ben Coppin, Ben Laurie, Andrew Senior, Nando de Freitas

To achieve this, we constructed the largest existing visual speech recognition dataset, consisting of pairs of text and video clips of faces speaking (3, 886 hours of video).

Ranked #10 on Lipreading on LRS3-TED (using extra training data)

Lipreading speech-recognition +1

Deep Reinforcement Learning in Large Discrete Action Spaces

2 code implementations24 Dec 2015 Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin

Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems.

Recommendation Systems reinforcement-learning +1

Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions

no code implementations3 Dec 2015 Peter Sunehag, Richard Evans, Gabriel Dulac-Arnold, Yori Zwols, Daniel Visentin, Ben Coppin

Further, we use deep deterministic policy gradients to learn a policy that for each position of the slate, guides attention towards the part of the action space in which the value is the highest and we only evaluate actions in this area.

Q-Learning Recommendation Systems

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