Tianshu Chu

Reinforcement Learning · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 19 citations into it
• Artificial Intelligence — 9 citations into it
• Control and Systems Engineering — 8 citations into it

Whom Tianshu Chu trusts overall

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

1. Marco A. Wiering
2. Ronald J. Williams
3. Csaba Szepesvari
4. Richard S. Sutton
5. Shalabh Bhatnagar
6. van der D David Pol
7. Volodymyr Mnih
8. Carlos Guestrin
9. John N. Tsitsiklis
10. Christopher J. C. H. Watkins

Who trusts Tianshu Chu overall

1. Hua Wei
2. Saeed Rahmani
3. Guanjie Zheng
4. Asiye Baghbani

Papers from Tianshu Chu's perspective

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

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Reinforcement Learning: An Introduction
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Human-level control through deep reinforcement learning
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Asynchronous Methods for Deep Reinforcement Learning

Their papers

• Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control (2019) — 870 citations
• An adaptive online learning framework for practical breast cancer diagnosis (2016) — 7 citations