Nan Zhao

Reinforcement Learning · with Jiang · 2019

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

Subfields

• Reinforcement Learning — 6 citations into it

Whom Nan Zhao trusts overall

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

1. Richard S. Sutton
2. Oshri Naparstek
3. Hado van Hasselt
4. Ursula Challita
5. Andrew Barto
6. Shangxing Wang
7. Kobi Cohen
8. David Silver
9. Arthur Guez
10. Li Dong

Papers from Nan Zhao's perspective

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

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

Their papers

• Deep Reinforcement Learning for User Association and Resource Allocation in Heterogeneous Cellular Networks (2019) — 385 citations