Hongyu Yang

Artificial Intelligence · with Rudin · 2016

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #11,194 of 35,345 by trust here, #16,771 by citations
• Statistical Learning Theory — 13 citations into it
• Information Systems — 12 citations into it; #1,962 of 8,771 by trust here, #3,098 by citations
• Computational Theory and Mathematics — 10 citations into it; #3,192 of 12,182 by trust here, #3,562 by citations
• Algorithms & Complexity — 9 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it; #716 of 1,525 by trust here, #817 by citations

Whom Hongyu Yang trusts overall

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

1. J. Ross Quinlan
2. William W. Cohen
3. Ryszard S. Michalski
4. Cynthia Rudin
5. Christophe G. Giraud-Carrier
6. Jadzia Cendrowska
7. Benjamin Letham
8. Peter Clark
9. B. Liu
10. Gary King

Who trusts Hongyu Yang overall

1. Cynthia Rudin
2. Tong Wang
3. Nadia Burkart
4. Elaine Angelino
5. Nicholas Larus-Stone
6. Danqing Pan
7. Xiyang Hu
8. Osbert Bastani
9. Clément Bénard
10. Francesco Bodria

Papers from Hongyu Yang's perspective

Ordered by how strongly the researchers Hongyu Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Scalable Bayesian Rule Lists (2016) — 232 citations