Shaoduo Gan
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 3 papers; trusts 54 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 67 citations into it; #30,319 of 35,345 by trust here, #15,236 by citations
- Optimization & Training — 64 citations into it
- Computer Networks and Communications — 33 citations into it; #8,404 of 9,886 by trust here, #3,155 by citations
- Computational Mechanics — 28 citations into it
- Computer Vision and Pattern Recognition — 21 citations into it
- ML Systems & Hardware — 19 citations into it
- Efficiency & Compression — 15 citations into it; #1,075 of 1,264 by trust here, #804 by citations
- Federated & Distributed Learning — 11 citations into it; #272 of 319 by trust here, #209 by citations
Whom Shaoduo Gan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Kaiming He
- Xiangru Lian
- Guanghui Lan
- Geoffrey E. Hinton
- Diederik P. Kingma
- Francis R. Bach
- Frank Torsten Bernd Seide
- Alex Krizhevsky
- Yoshua Bengio
Who trusts Shaoduo Gan overall
- Hanlin Tang
- Anastasia Koloskova
- Chaoyang He
- Navjot Singh
- Qinyi Luo
- Zhenheng Tang
- Sebastian U. Stich
- Farzin Haddadpour
- Xiang Li
- Yuanming Shi
Papers from Shaoduo Gan's perspective
Ordered by how strongly the researchers Shaoduo Gan trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- 1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed (2021) — 111 citations
- Communication Compression for Decentralized Training (2018) — 314 citations
- Decentralization Meets Quantization (2018) — 17 citations