Ching-An Cheng

Reinforcement Learning · with Agarwal · 2021

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 24 citations into it
• Artificial Intelligence — 22 citations into it
• Management Science and Operations Research — 9 citations into it
• Statistical Learning Theory — 8 citations into it

Whom Ching-An Cheng trusts overall

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

1. R´emi Munos
2. Csaba Szepesvari
3. Sham M. Kakade
4. Richard S. Sutton
5. Nan Jiang
6. Alekh Agarwal
7. Andrea Zanette
8. Yao Liu
9. Dimitri P. Bertsekas
10. J. Langford

Who trusts Ching-An Cheng overall

1. Audrey Huang
2. Masatoshi Uehara

Papers from Ching-An Cheng's perspective

Ordered by how strongly the researchers Ching-An Cheng 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. Human-level control through deep reinforcement learning
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Bellman-consistent Pessimism for Offline Reinforcement Learning (2021) — 335 citations