Tianhong Dai

Reinforcement Learning · with Du · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 21 citations into it; #2,044 of 2,242 by trust here, #1,999 by citations
• Artificial Intelligence — 20 citations into it
• Optimization & Training — 5 citations into it

Whom Tianhong Dai trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. John Schulman

Who trusts Tianhong Dai overall

1. Tabish Rashid

Papers from Tianhong Dai's perspective

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

1. Reinforcement Learning: An Introduction
2. Proximal Policy Optimization Algorithms (arXiv.org)
3. Trust Region Policy Optimization (International Conference on Machine Learning)
4. Curiosity-Driven Exploration by Self-Supervised Prediction
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Learning to learn by gradient descent by gradient descent
7. ImageNet classification with deep convolutional neural networks
8. Long Short-Term Memory
9. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
10. ViZDoom: A Doom-based AI research platform for visual reinforcement learning

Their papers

• LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning (2019) — 194 citations