Shengyuan Hu

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #31,209 of 35,345 by trust here, #26,682 by citations
• Federated & Distributed Learning — 26 citations into it
• Safety, Robustness & Interpretability — 16 citations into it
• Optimization & Training — 9 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Shengyuan Hu trusts overall

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

1. Battista Biggio
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. H. Brendan McMahan
5. Yoshua Bengio
6. Tian Li
7. Mehryar Mohri
8. Diederik P. Kingma
9. Yann LeCun
10. Virginia Smith

Who trusts Shengyuan Hu overall

1. Sang-Min Park
2. Jaehoon Oh
3. Mang Ye

Papers from Shengyuan Hu's perspective

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

Their papers

• Ditto: Fair and Robust Federated Learning Through Personalization (2020) — 1,411 citations