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Demonstration
MoGo: exploration-exploitation in Monte-Carlo Go using UCT and patterns
Olivier Teytaud · Sylvain Gelly
Author Information
Olivier Teytaud (TAO (Inria))
Sylvain Gelly (Google Brain (Zurich))
More from the Same Authors
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2020 Poster: What Do Neural Networks Learn When Trained With Random Labels? »
Hartmut Maennel · Ibrahim Alabdulmohsin · Ilya Tolstikhin · Robert Baldock · Olivier Bousquet · Sylvain Gelly · Daniel Keysers -
2020 Spotlight: What Do Neural Networks Learn When Trained With Random Labels? »
Daniel Keysers · Sylvain Gelly · Olivier Bousquet · Robert Baldock · Ilya Tolstikhin · Ibrahim Alabdulmohsin · Hartmut Maennel -
2019 Poster: Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates »
Carlos Riquelme · Hugo Penedones · Damien Vincent · Hartmut Maennel · Sylvain Gelly · Timothy A Mann · Andre Barreto · Gergely Neu -
2018 Poster: Assessing Generative Models via Precision and Recall »
Mehdi S. M. Sajjadi · Olivier Bachem · Mario Lucic · Olivier Bousquet · Sylvain Gelly -
2018 Poster: Are GANs Created Equal? A Large-Scale Study »
Mario Lucic · Karol Kurach · Marcin Michalski · Sylvain Gelly · Olivier Bousquet -
2017 Poster: AdaGAN: Boosting Generative Models »
Ilya Tolstikhin · Sylvain Gelly · Olivier Bousquet · Carl-Johann SIMON-GABRIEL · Bernhard Schölkopf
