Gang Chen

Artificial Intelligence · with Chen · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Information Systems — 19 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Recommender Systems — 9 citations into it
• Management Science and Operations Research — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Gang Chen trusts overall

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

1. Diederik P. Kingma

Papers from Gang Chen's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Caffe: Convolutional Architecture for Fast Feature Embedding

Their papers

• Robust Federated Recommendation System (2020) — 33 citations
• Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification (2019) — 41 citations