YeeMan Bergstrom

Reinforcement Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 9 citations into it
• Management Science and Operations Research — 6 citations into it
• Finance — 5 citations into it

Whom YeeMan Bergstrom trusts overall

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

1. Richard S. Sutton
2. Michail G. Lagoudakis
3. Nan Jiang
4. Adith Swaminathan
5. Rama Cont
6. James M. Robins
7. Jianqing Fan
8. Lihong Li
9. Andrew Barto
10. Miroslav Dud'ik

Papers from YeeMan Bergstrom's perspective

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

1. Reinforcement Learning: An Introduction
2. Least-Squares Policy Iteration
3. Doubly Robust Off-policy Value Evaluation for Reinforcement Learning
4. Q-learning
5. ImageNet classification with deep convolutional neural networks
6. Dynamic Programming and Optimal Control. Volume 1
7. Gradient-based learning applied to document recognition
8. Estimation of Regression Coefficients When Some Regressors are not Always Observed
9. Human-level control through deep reinforcement learning
10. Doubly Robust Policy Evaluation and Optimization

Their papers

• Data-Driven Market-Making via Model-Free Learning (2020) — 132 citations