Anton Schwartz

Reinforcement Learning · 1993–1999

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 12 citations into it; #525 of 2,242 by trust here, #1,319 by citations

Whom Anton Schwartz trusts overall

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

1. Richard S. Sutton
2. Satinder Singh
3. Andrew W. Moore
4. Tommi S. Jaakkola
5. Martin L. Puterman
6. Justin A. Boyan
7. Andrew Barto
8. David E. Rumelhart
9. Geoffrey E. Hinton
10. Leslie Pack Kaelbling

Who trusts Anton Schwartz overall

1. Sridhar Mahadevan
2. J. Urgen Schmidhuber
3. Michael L. Littman
4. Hado van Hasselt
5. Andrew Barto
6. Abhijit Gosavi
7. Richard S. Sutton
8. Pierre-Yves Glorennec
9. Satinder Singh
10. Tommi S. Jaakkola

Papers from Anton Schwartz's perspective

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

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

Their papers

• Issues in Using Function Approximation for Reinforcement Learning (1999)
• Finding Structure in Reinforcement Learning (1994)
• A Reinforcement Learning Method for Maximizing Undiscounted Rewards (1993)