Chao-Kai Chiang

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it; #5,579 of 35,345 by trust here, #4,466 by citations
• Computational Mechanics — 14 citations into it
• Optimization & Training — 12 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Chao-Kai Chiang trusts overall

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

1. Shai Shalev-Shwartz
2. H. Brendan McMahan
3. Jakub Konecný
4. Yu Zhang
5. Jiayu Zhou
6. Geoffrey E. Hinton
7. Andreas Argyriou
8. Theodoros Evgeniou
9. Martin Jaggi
10. Francis R. Bach

Who trusts Chao-Kai Chiang overall

1. Tian Li
2. Anit Kumar Sahu
3. Alireza Fallah
4. Virginia Smith
5. Li Li
6. Aryan Mokhtari
7. Ameet Talwalkar
8. Luping Wang
9. Tribhuvanesh Orekondy
10. Sebastian Caldas

Papers from Chao-Kai Chiang's perspective

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

Their papers

• Federated Multi-Task Learning (2017) — 2,150 citations