Wooi-Boon Goh

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 12 citations into it

Whom Wooi-Boon Goh trusts overall

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

1. Ronald J. Williams
2. John Schulman
3. Richard S. Sutton
4. Sergey Levine
5. David Silver
6. E. Todorov
7. Tom Schaul
8. Volodymyr Mnih
9. Geoffrey E. Hinton
10. Shixiang Shane Gu

Who trusts Wooi-Boon Goh overall

1. Yaqian Zhang

Papers from Wooi-Boon Goh's perspective

Ordered by how strongly the researchers Wooi-Boon Goh trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Bootstrapped Policy Gradient for Difficulty Adaptation in Intelligent Tutoring Systems (2019) — 4 citations