Liang Yu

Reinforcement Learning · with Zhang · 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 — 26 citations into it

Whom Liang Yu trusts overall

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

1. Richard S. Sutton
2. Tianshu Wei
3. Andrew Barto
4. Zhe Wang
5. Renzhi Lu
6. Volodymyr Mnih
7. Tejas D. Kulkarni
8. Yanzhi Wang
9. Geoffrey E. Hinton
10. Zhuangdi Zhu

Who trusts Liang Yu overall

1. Xin Chen

Papers from Liang Yu's perspective

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

Their papers

• Deep Reinforcement Learning for Smart Home Energy Management (2019) — 382 citations
• A Review of Deep Reinforcement Learning for Smart Building Energy Management (2020) — 357 citations