Xinle Liang

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Federated & Distributed Learning — 14 citations into it
• Privacy & Security — 11 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Xinle Liang trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Karen Simonyan
6. Yoshua Bengio
7. Yann LeCun
8. Diederik P. Kingma
9. Cynthia Dwork
10. Ilya Sutskever

Papers from Xinle Liang's perspective

Ordered by how strongly the researchers Xinle Liang 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Self-supervised Cross-silo Federated Neural Architecture Search (2021) — 21 citations
• Federated Transfer Reinforcement Learning for Autonomous Driving (2019) — 131 citations