Puay Siew Tan

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it

Whom Puay Siew Tan trusts

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

1. Risto Miikkulainen (in Artificial Intelligence)
2. J. Urgen Schmidhuber (in Artificial Intelligence)
3. Kenneth O. Stanley (in Artificial Intelligence)
4. Pedro Larrañaga (in Artificial Intelligence)

Papers from Puay Siew Tan's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. Human-level control through deep reinforcement learning
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Multitask Learning
6. Proximal Policy Optimization Algorithms (arXiv.org)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Multifactorial Evolutionary Algorithm With Online Transfer Parameter Estimation: MFEA-II (2020) — 372 citations
• Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning (2020) — 463 citations