Kam-Fai Wong

Artificial Intelligence · 2008–2018

A researcher in the Science corpus: 11 papers; trusts 145 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 139 citations into it; #9,293 of 35,345 by trust here, #6,911 by citations
• Natural Language Processing — 100 citations into it; #3,199 of 5,688 by trust here, #4,032 by citations
• Sociology and Political Science — 37 citations into it; #2,355 of 22,756 by trust here, #5,006 by citations
• Information Systems — 36 citations into it; #2,612 of 8,771 by trust here, #2,821 by citations
• Statistical and Nonlinear Physics — 31 citations into it; #8,008 of 10,127 by trust here, #3,513 by citations
• Computer Vision and Pattern Recognition — 28 citations into it
• Reinforcement Learning — 26 citations into it
• Model Architectures — 23 citations into it

Whom Kam-Fai Wong trusts overall

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

1. Yoshua Bengio
2. Richard Socher
3. Geoffrey E. Hinton
4. Alex Graves
5. Chin-Yew Lin
6. Ilya Sutskever
7. Sepp Hochreiter
8. Jing Ma
9. Ronald J. Williams
10. Diederik P. Kingma

Who trusts Kam-Fai Wong overall

1. Rushdi Shams
2. Ani Nenkova
3. Jing Ma
4. Marina Litvak
5. Yue Dong
6. Ramesh Nallapati
7. Yi-Ju Lu
8. Mehdi Allahyari
9. Tian Bian
10. Karishma Sharma

Papers from Kam-Fai Wong's perspective

Ordered by how strongly the researchers Kam-Fai Wong 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Towards Neural Network-based Reasoning (2015) — 75 citations
• Extractive Summarization Using Supervised and Semi-Supervised Learning (2008) — 238 citations
• Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning (2017) — 195 citations
• Detect Rumors Using Time Series of Social Context Information on Microblogging Websites (2015) — 672 citations
• Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning (2017) — 642 citations
• Rumor Detection on Twitter with Tree-structured Recursive Neural Networks (2018) — 596 citations
• Task-oriented Dialogue System for Automatic Diagnosis (2018) — 245 citations
• Detecting Rumors from Microblogs with Recurrent Neural Networks (2016) — 1,331 citations
• An Attentional Neural Conversation Model with Improved Specificity (2016) — 31 citations
• Recurrent Neural Networks with External Memory for Spoken Language Understanding (2015) — 49 citations
• Interpreting TF-IDF term weights as making relevance decisions (2008) — 872 citations