Shuai Wang

Artificial Intelligence · with Liu · 2016–2020

A researcher in the Science corpus: 9 papers; trusts 294 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 245 citations into it; #6,112 of 35,345 by trust here, #9,557 by citations
• Natural Language Processing — 143 citations into it; #3,196 of 5,688 by trust here, #4,793 by citations
• Computer Vision and Pattern Recognition — 53 citations into it
• Representation & Self-Supervised Learning — 48 citations into it; #2,063 of 3,145 by trust here, #2,863 by citations
• Information Systems — 26 citations into it
• Meta & Continual Learning — 25 citations into it; #404 of 1,041 by trust here, #782 by citations
• Reinforcement Learning — 17 citations into it
• Model Architectures — 16 citations into it

Whom Shuai Wang trusts overall

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

1. Zhiyuan Chen
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. B. Liu
5. Diederik P. Kingma
6. Alex Graves
7. Richard Socher
8. Alex Krizhevsky
9. Sebastian Thrun
10. Ilya Sutskever

Who trusts Shuai Wang overall

1. Bing Liu
2. Zixuan Ke
3. Hu Xu
4. Lei Shu
5. Sahisnu Mazumder
6. Qi Qin
7. Wenpeng Hu
8. Aytuğ Onan
9. Dogu Araci
10. Jason Ramapuram

Papers from Shuai Wang's perspective

Ordered by how strongly the researchers Shuai Wang 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Deep learning for sentiment analysis: A survey (2018) — 1,916 citations
• An Application-Independent Approach to Building Task-Oriented Chatbots with Interactive Continual Learning (2020)
• Continuous and Interactive Factual Knowledge Learning in Verification Dialogues (2020)
• Sentiment Classification by Leveraging the Shared Knowledge from a Sequence of Domains (2019) — 44 citations
• Forward and Backward Knowledge Transfer for Sentiment Classification (2019) — 18 citations
• Lifelong and Interactive Learning of Factual Knowledge in Dialogues (2019) — 28 citations
• Lifelong Learning Memory Networks for Aspect Sentiment Classification (2018) — 30 citations
• Learning Cumulatively to Become More Knowledgeable (2016) — 103 citations
• Mining Aspect-Specific Opinion using a Holistic Lifelong Topic Model (2016) — 135 citations