Wenfeng Feng

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Reinforcement Learning — 21 citations into it
• Optimization & Training — 6 citations into it
• Privacy & Security — 5 citations into it

Whom Wenfeng Feng trusts overall

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

1. H. Brendan McMahan
2. Aviv Tamar
3. Cynthia Dwork
4. Matthew E. Taylor
5. Volodymyr Mnih
6. Sergey Levine
7. Richard S. Sutton
8. Pieter Abbeel
9. Jakub Konecný
10. Geoffrey E. Hinton

Papers from Wenfeng Feng's perspective

Ordered by how strongly the researchers Wenfeng Feng 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Human-level control through deep reinforcement learning
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Federated Deep Reinforcement Learning (2019) — 106 citations
• Federated Reinforcement Learning (2019) — 84 citations