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Publications
Information Theory
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Publication
Learning more skills through optimistic exploration
DJ Strouse, Kate Baumli, David Warde-Farley, Vlad Mnih, Steven Hansen
ICLR
2022-01-28
Deep reinforcement learning
Information Theory
Unsupervised learning & generative models
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Publication
Gaussian dropout as an information bottleneck layer
Mélanie Rey, Andriy Mnih
NeurIPS Workshop
2021-12-14
Information Theory
Unsupervised learning & generative models
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Publication
Fast active learning for pure exploration in reinforcement learning
Pierre Ménard *, O Domingues *, Emilie Kaufmann *, Anders Jonsson *, Edouard Leurent *, Michal Valko
ICML
2021-07-18
Online Learning
Theory & foundations
Information Theory
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Publication
Information Theoretic Meta Learning with Gaussian Processes
Michalis Titsias, Sotirios Nikoloutsopoulos *, Alexandre Galashov
arXiv
2020-09-07
Meta-Learning
Information Theory
Probabilistic learning
Memory
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Publication
Action and Perception as Divergence Minimization
Danijar Hafner *, Pedro A. Ortega, Jimmy Ba *, Thomas Parr *, Karl Friston *, Nicolas Heess
arXiv
2020-09-03
Reinforcement learning
Information Theory
Unsupervised learning & generative models
Probabilistic learning
Theory & foundations
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Publication
Making Sense of Reinforcement Learning and Probabilistic Inference
Brendan O'Donoghue, Ian Osband, Catalin Ionescu
ICLR
2020-01-03
Reinforcement learning
Theory & foundations
Deep reinforcement learning
Information Theory
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Publication
A Mutual Information Maximization Perspective of Language Representation Learning
Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling, Lei Yu, Z Dai *, Dani Yogatama
arXiv
2019-10-18
Language
Information Theory
Deep learning
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Publication
Exact sampling of determinantal point processes with sublinear time preprocessing
Michal Dereziński *, Daniele Calandriello *, Michal Valko
NeurIPS
2019-05-31
Information Theory
Online Learning
Probabilistic learning
Representation learning
Theory & foundations
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Publication
Online Learning with Gated Linear Networks
Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth
arXiv
2017-12-08
Deep learning
Information Theory
Online Learning
Probabilistic learning
Theory & foundations
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Publication
Compress and Control
Joel Veness, Marc Gendron-Bellemare, M Hutter *, Alvin Chua, Guillaume Desjardins
AAAI
2015-01-01
Games
Information Theory
Reinforcement learning
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Publication
Skip Context Tree Switching
Marc Gendron-Bellemare, Joel Veness, E Talvitie *
ICML
2014-01-01
Information Theory
Online Learning
Probabilistic learning
Theory & foundations
Download
Publication
Online Learning of k-CNF Boolean Functions
Joel Veness, M Hutter *, Laurent Orseau, Marc Gendron-Bellemare
IJCAI
2014-01-01
Information Theory
Online Learning
Theory & foundations
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