Jinglin Chen

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 31 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 27 citations into it; #544 of 2,242 by trust here, #1,344 by citations
• Artificial Intelligence — 17 citations into it; #6,115 of 35,345 by trust here, #15,236 by citations
• Statistical Learning Theory — 9 citations into it
• Management Science and Operations Research — 9 citations into it
• Control and Systems Engineering — 6 citations into it

Whom Jinglin Chen trusts overall

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

1. R´emi Munos
2. Csaba Szepesvari
3. Dimitri P. Bertsekas
4. Richard S. Sutton
5. B. '. Pires
6. Lihong Li
7. Andrew Barto
8. Ward Whitt
9. Sham M. Kakade
10. Odalric-Ambrym Maillard

Who trusts Jinglin Chen overall

1. Ruosong Wang
2. Tengyang Xie
3. Nan Jiang
4. Simon Shaolei Du
5. Zhuoran Yang
6. Sham M. Kakade
7. Chi Jin
8. Alekh Agarwal
9. Ming Yin
10. Xinkun Nie

Papers from Jinglin Chen's perspective

Ordered by how strongly the researchers Jinglin Chen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Human-level control through deep reinforcement learning
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Information-Theoretic Considerations in Batch Reinforcement Learning (2019) — 421 citations