Yu Luo

Artificial Intelligence · with Huang · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Federated & Distributed Learning — 10 citations into it

Whom Yu Luo trusts overall

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

1. H. Brendan McMahan
2. Cynthia Dwork
3. Joseph Redmon
4. Ross B. Girshick
5. Yang Liu
6. Shaoqing Ren
7. Kaiming He
8. Geoffrey E. Hinton
9. Alex Krizhevsky

Papers from Yu Luo's perspective

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

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

Their papers

• FedVision: An Online Visual Object Detection Platform Powered by Federated Learning (2020) — 352 citations
• Real-World Image Datasets for Federated Learning (2019) — 111 citations