Xueguang Lu

Reinforcement Learning · 2018

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 21 citations into it
• Artificial Intelligence — 12 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Xueguang Lu trusts overall

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

1. Chris Amato
2. Sepp Hochreiter
3. Christopher J. C. H. Watkins
4. Laëtitia Matignon
5. Matthew J. Hausknecht
6. Martin Lauer
7. Will Dabney
8. Liviu Panait
9. Richard S. Sutton
10. J. Urgen Schmidhuber

Papers from Xueguang Lu's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Reinforcement Learning: An Introduction
7. Human-level control through deep reinforcement learning
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Decentralized Likelihood Quantile Networks for Improving Performance in Deep Multi-Agent Reinforcement Learning (2018)