Kuo-Yi Lin

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 103 citations into it
• Federated & Distributed Learning — 63 citations into it
• Privacy & Security — 20 citations into it
• Computer Science Applications — 18 citations into it
• Electrical and Electronic Engineering — 15 citations into it
• Computer Networks and Communications — 10 citations into it
• Efficiency & Compression — 6 citations into it
• Medical & Health AI — 6 citations into it

Whom Kuo-Yi Lin trusts overall

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

1. Li Huang
2. Dianbo Liu
3. H. Brendan McMahan
4. Milad Nasr
5. Virginia Smith
6. Swaroop Indra Ramaswamy
7. Eugene Bagdasarian
8. Yang Liu
9. Geoffrey E. Hinton
10. Takayuki Nishio

Papers from Kuo-Yi Lin's perspective

Ordered by how strongly the researchers Kuo-Yi Lin 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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Survey on federated learning* (2020) — 878 citations
• A review of applications in federated learning (2020) — 1,458 citations