Ling Zhu

Artificial Intelligence · with Deb · 2020

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Reinforcement Learning — 13 citations into it
• Computational Theory and Mathematics — 9 citations into it

Whom Ling Zhu trusts overall

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

1. Kalyanmoy Deb
2. Richard S. Sutton
3. Marek Kretowski
4. Daniel Hein

Papers from Ling Zhu's perspective

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

1. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
2. Asynchronous Methods for Deep Reinforcement Learning
3. Trust Region Policy Optimization (International Conference on Machine Learning)
4. Proximal Policy Optimization Algorithms (arXiv.org)
5. Deep Reinforcement Learning with Double Q-Learning
6. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
7. Tree-Based Batch Mode Reinforcement Learning
8. On-line Q-learning using connectionist systems
9. Relative Entropy Policy Search
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• Toward Interpretable-AI Policies Using Evolutionary Nonlinear Decision Trees for Discrete-Action Systems (2020) — 20 citations