Li Li

Computer Vision and Pattern Recognition · with Xu · 2022

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Li Li trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Yann LeCun

Papers from Li Li's perspective

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

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Learning Multiple Layers of Features from Tiny Images
4. ImageNet classification with deep convolutional neural networks
5. GradientBased Learning Applied to Document Recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction (2022) — 423 citations