Yeounoh Chung

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Management Science and Operations Research — 17 citations into it
• Optimization & Training — 10 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Computer Networks and Communications — 6 citations into it
• Computer Science Applications — 6 citations into it
• Information Systems — 5 citations into it

Whom Yeounoh Chung trusts overall

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

1. Jiannan Wang
2. M. Franklin
3. Adam Marcus
4. Gregory Valiant
5. Lise Getoor
6. Tim Kraska
7. Qiang Liu
8. Brian Babcock
9. Ziawasch Abedjan
10. Paul Valiant

Papers from Yeounoh Chung's perspective

Ordered by how strongly the researchers Yeounoh Chung 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. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Going deeper with convolutions
10. Et al

Their papers

• Democratizing Data Science through Interactive Curation of ML Pipelines (2019) — 107 citations
• A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets (2016) — 21 citations