Haitao Mi
Natural Language Processing · with Wang · 2015–2016
A researcher in the Science corpus: 6 papers; trusts 169 researchers and is trusted by 49 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 76 citations into it; #1,074 of 5,688 by trust here, #1,721 by citations
- Artificial Intelligence — 75 citations into it; #4,532 of 35,345 by trust here, #7,531 by citations
- Computer Vision and Pattern Recognition — 28 citations into it; #4,650 of 21,575 by trust here, #6,089 by citations
- Model Architectures — 18 citations into it
- Evaluation & Benchmarks — 9 citations into it
- Optimization & Training — 9 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
- Molecular Biology — 5 citations into it
Whom Haitao Mi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matthew D. Zeiler
- Kyunghyun Cho
- Yoshua Bengio
- Geoffrey E. Hinton
- Dzmitry Bahdanau
- Ilya Sutskever
- Diederik P. Kingma
- Oriol Vinyals
- Alex Krizhevsky
- Alex Graves
Who trusts Haitao Mi overall
- Jun Suzuki
- Zhiguo Wang
- Jonas Gehring
- Minghao Hu
- Markus Freitag
- Abigail See
- Philip Arthur
- Masaaki Nagata
- Marcin Junczys-Dowmunt
- Linfeng Song
Papers from Haitao Mi's perspective
Ordered by how strongly the researchers Haitao Mi trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Multi-Perspective Context Matching for Machine Comprehension (2016) — 158 citations
- Vocabulary Manipulation for Neural Machine Translation (2016) — 67 citations
- Temporal Attention Model for Neural Machine Translation (2016) — 63 citations
- Sentence Similarity Learning by Lexical Decomposition and Composition (2016) — 207 citations
- Coverage Embedding Models for Neural Machine Translation (2016) — 159 citations
- Feature Optimization for Constituent Parsing via Neural Networks (2015) — 20 citations