Yue Tan

Artificial Intelligence · AAAI Conference on Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 62 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 112 citations into it
• Federated & Distributed Learning — 40 citations into it
• Computer Vision and Pattern Recognition — 37 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Computer Science Applications — 14 citations into it
• Optimization & Training — 13 citations into it
• Information Systems — 10 citations into it
• Model Architectures — 6 citations into it

Whom Yue Tan trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Yann LeCun
6. Karen Simonyan
7. Yoshua Bengio
8. Ilya Sutskever
9. Andrew Zisserman
10. Guodong Long

Who trusts Yue Tan overall

1. Guodong Long

Papers from Yue Tan's perspective

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

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

Their papers

• Federated Learning from Pre-Trained Models: A Contrastive Learning Approach (2022) — 296 citations
• FedProto: Federated Prototype Learning across Heterogeneous Clients (2021) — 940 citations
• Federated Learning for Open Banking (2021) — 370 citations