Olivier Buffet

Reinforcement Learning · 2001–2012

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 18 citations into it
• Artificial Intelligence — 11 citations into it; #11,334 of 35,345 by trust here, #25,809 by citations
• Statistical Learning Theory — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Olivier Buffet trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Malcolm J. A. Strens
3. Andrew Barto
4. Ronen I. Brafman
5. J. Kolter
6. Satinder Singh
7. Jonathan Sorg
8. Andrew Y. Ng
9. Pascal Poupart
10. Michael L. Littman

Who trusts Olivier Buffet overall

1. Brendan O'Donoghue
2. Kenji Kawaguchi
3. Ian Osband
4. Yasin Abbasi-Yadkori
5. Sergey Levine
6. Bradly C. Stadie
7. Raphael Fonteneau
8. Teodor Mihai Moldovan
9. Shayegan Omidshafiei
10. Marc G. Bellemare

Papers from Olivier Buffet's perspective

Ordered by how strongly the researchers Olivier Buffet trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. Markov Decision Processes: Discrete Stochastic Dynamic Programming
3. Gradient-based learning applied to document recognition
4. ImageNet classification with deep convolutional neural networks
5. Near-Optimal Reinforcement Learning in Polynomial Time
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
8. A Bayesian Framework for Reinforcement Learning
9. Long Short-Term Memory
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Near-Optimal BRL using Optimistic Local Transitions (2012) — 41 citations
• Multi-Agent Systems by Incremental Gradient Reinforcement Learning (2001) — 45 citations