Gen Li

Reinforcement Learning · with Chen · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 15 citations into it

Whom Gen Li trusts overall

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

1. John N. Tsitsiklis
2. Csaba Szepesvari
3. Ben J. A. Kröse
4. Richard S. Sutton
5. Vivek Shripad Borkar
6. Eyal Even-Dar
7. Tommi S. Jaakkola
8. Rie Johnson
9. Lin F. Yang
10. Devavrat Shah

Who trusts Gen Li overall

1. Ming Yin
2. Xin Chen
3. Brendan O'Donoghue
4. Yu Bai

Papers from Gen Li's perspective

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

Their papers

• Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction (2020) — 145 citations
• Nonconvex Low-Rank Tensor Completion from Noisy Data (2019) — 95 citations