Hongyuan Zhan

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 77 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 96 citations into it
• Optimization & Training — 46 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Federated & Distributed Learning — 31 citations into it
• Efficiency & Compression — 17 citations into it
• Natural Language Processing — 10 citations into it
• Electrical and Electronic Engineering — 7 citations into it

Whom Hongyuan Zhan trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. Karen Simonyan
9. Jimmy Ba
10. Ruslan Salakhutdinov

Papers from Hongyuan Zhan's perspective

Ordered by how strongly the researchers Hongyuan Zhan 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Evaluating Lottery Tickets Under Distributional Shifts (2019) — 42 citations
• Papaya: Practical, Private, and Scalable Federated Learning (2021) — 172 citations
• Federated Learning with Buffered Asynchronous Aggregation (2021) — 469 citations