Chenjun Xiao

Reinforcement Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 11 citations into it

Whom Chenjun Xiao trusts overall

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

1. Ronald J. Williams
2. Sham M. Kakade
3. Yurii E. Nesterov
4. John Schulman
5. Richard S. Sutton
6. David Silver
7. Alekh Agarwal
8. Sergey Levine
9. Geoffrey E. Hinton

Who trusts Chenjun Xiao overall

1. Ben M. Hambly

Papers from Chenjun Xiao's perspective

Ordered by how strongly the researchers Chenjun Xiao 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. Asynchronous Methods for Deep Reinforcement Learning
4. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Trust Region Policy Optimization (International Conference on Machine Learning)
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Proximal Policy Optimization Algorithms (arXiv.org)

Their papers

• On the Global Convergence Rates of Softmax Policy Gradient Methods (2020) — 369 citations