Abhijit Gosavi

Reinforcement Learning · 2003–2009

A researcher in the Science corpus: 3 papers; trusts 38 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 49 citations into it
• Artificial Intelligence — 22 citations into it; #9,546 of 35,345 by trust here, #24,417 by citations
• Computer Networks and Communications — 8 citations into it; #3,958 of 9,886 by trust here, #7,492 by citations
• Statistical Learning Theory — 6 citations into it
• Management Science and Operations Research — 5 citations into it; #4,903 of 11,946 by trust here, #8,469 by citations
• Statistics and Probability — 5 citations into it

Whom Abhijit Gosavi trusts overall

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

1. Vivek Shripad Borkar
2. Andrew Barto
3. Richard S. Sutton
4. Michael L. Littman
5. Anton Schwartz
6. Eric R. Ziegel
7. J. Ross Quinlan
8. Sridhar Mahadevan
9. Harold J. Kushner
10. Steven J. Bradtke

Who trusts Abhijit Gosavi overall

1. Dimitri P. Bertsekas
2. Francisco Silva
3. F. Ingrand
4. Csaba Szepesvari
5. Tom Erez
6. Huizhen Yu
7. Ivo Grondman
8. R´emi Munos
9. Malik Ghallab
10. Yuval Tassa

Papers from Abhijit Gosavi's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• A Reinforcement Learning Algorithm Based on Policy Iteration for Average Reward: Empirical Results with Yield Management and Convergence Analysis (2004) — 91 citations
• Reinforcement Learning: A Tutorial Survey and Recent Advances (2009) — 357 citations
• Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning (2003) — 528 citations