Hui-Ching Lin

Artificial Intelligence · 2009–2012

A researcher in the Science corpus: 4 papers; trusts 43 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #10,677 of 35,345 by trust here, #17,110 by citations
• Computational Theory and Mathematics — 13 citations into it
• Natural Language Processing — 13 citations into it; #1,544 of 5,688 by trust here, #3,014 by citations
• Optimization & Training — 9 citations into it
• Computer Graphics and Computer-Aided Design — 6 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Hui-Ching Lin trusts overall

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

1. Chin-Yew Lin
2. Maxim Sviridenko
3. Andreas Krause
4. B. Taskar
5. Ryan T. McDonald
6. Rada Mihalcea
7. Carlos Guestrin
8. Dekang Lin
9. Adwait Ratnaparkhi
10. Hoa Trang Dang

Who trusts Hui-Ching Lin overall

1. Niv Buchbinder
2. J. Bilmes
3. Kai Hong
4. Moran Feldman
5. Jin-ge Yao
6. Li Deng
7. Kai Hong
8. Parth Mehta
9. Rishabh K. Iyer
10. Alex Kulesza

Papers from Hui-Ching Lin's perspective

Ordered by how strongly the researchers Hui-Ching Lin trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• A study on multilingual acoustic modeling for large vocabulary ASR (2009) — 130 citations
• Learning Mixtures of Submodular Shells with Application to Document Summarization (2012) — 203 citations
• A Class of Submodular Functions for Document Summarization (2011) — 863 citations
• Multi-document Summarization via Budgeted Maximization of Submodular Functions (2010) — 418 citations