Kenglun Chang

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Federated & Distributed Learning — 5 citations into it

Whom Kenglun Chang trusts overall

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

1. Praneeth Vepakomma
2. Robert A. Jacobs
3. Yann LeCun
4. Adam Coates
5. Otkrist Gupta
6. Ramesh Raskar
7. Geoffrey E. Hinton
8. Matthew Tancik
9. Yoshua Bengio
10. David D. Lewis

Papers from Kenglun Chang's perspective

Ordered by how strongly the researchers Kenglun Chang 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. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
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. Going deeper with convolutions

Their papers

• ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations (2019) — 11 citations
• ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries (2019) — 7 citations