Hao Liang

Artificial Intelligence · with Joshi · 2020

A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Optimization & Training — 47 citations into it
• Federated & Distributed Learning — 24 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• ML Systems & Hardware — 17 citations into it
• Computer Networks and Communications — 9 citations into it
• Electrical and Electronic Engineering — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Hao Liang trusts overall

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

1. Alex Krizhevsky
2. Sebastian U. Stich
3. Diederik P. Kingma
4. Kaiming He
5. Geoffrey E. Hinton
6. Jianyu Wang
7. Ilya Sutskever
8. Hao Yu
9. Yann LeCun
10. Karen Simonyan

Papers from Hao Liang's perspective

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

Their papers

• Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization (2020) — 2,059 citations
• Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD (2020) — 35 citations