Feng Lyu

Reinforcement Learning · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 6 citations into it

Whom Feng Lyu trusts overall

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

1. Ronald J. Williams
2. David Silver
3. Hado van Hasselt
4. Seongah Jeong

Papers from Feng Lyu's perspective

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

1. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
2. Asynchronous Methods for Deep Reinforcement Learning
3. Deep Reinforcement Learning with Double Q-Learning
4. Deterministic Policy Gradient Algorithms
5. End to End Learning for Self-Driving Cars
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. Vision meets robotics: The KITTI dataset
10. Long Short-Term Memory

Their papers

• Internet of vehicles in big data era (2018) — 469 citations
• Space/Aerial-Assisted Computing Offloading for IoT Applications: A Learning-Based Approach (2019) — 764 citations