Ping Li

Artificial Intelligence · with Huang · 2023

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Optimization & Training — 22 citations into it
• Federated & Distributed Learning — 18 citations into it
• Computational Mechanics — 12 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Electrical and Electronic Engineering — 5 citations into it
• ML Systems & Hardware — 5 citations into it

Whom Ping Li trusts overall

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

1. Sebastian U. Stich
2. Yurii E. Nesterov
3. Hao Yu
4. Yann LeCun
5. Sai Praneeth Karimireddy
6. Alex Krizhevsky
7. Yanli Liu
8. Dan Alistarh
9. Geoffrey E. Hinton
10. Anastasia Koloskova

Papers from Ping Li's perspective

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

Their papers

• Stochastic Controlled Averaging for Federated Learning with Communication Compression (2023) — 308 citations