Scott Yang

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Optimization & Training — 19 citations into it
• Management Science and Operations Research — 15 citations into it
• Natural Language Processing — 10 citations into it
• Statistical Learning Theory — 7 citations into it

Whom Scott Yang trusts overall

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

1. Mehryar Mohri
2. Manfred K. Warmuth
3. Nicolò Cesa-Bianchi
4. Nick Littlestone
5. Mark Herbster
6. Jyrki Kivinen
7. Claire Monteleoni
8. Tim van Erven
9. Peter Auer
10. Robert D. Kleinberg

Who trusts Scott Yang overall

1. Fei Ye
2. Yawei Zhao

Papers from Scott Yang's perspective

Ordered by how strongly the researchers Scott Yang 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. Going deeper with convolutions
4. Gradient-based learning applied to document recognition
5. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Structured Prediction Theory Based on Factor Graph Complexity (2016) — 62 citations
• Competing with Automata-based Expert Sequences (2018) — 9 citations
• AdaNet: Adaptive Structural Learning of Artificial Neural Networks (2016) — 301 citations