Ke Wang

Artificial Intelligence · with Tang · 2018

A researcher in the Science corpus: 2 papers; trusts 156 researchers and is trusted by 51 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it; #4,131 of 35,345 by trust here, #11,192 by citations
• Information Systems — 33 citations into it; #404 of 8,771 by trust here, #1,895 by citations
• Computer Vision and Pattern Recognition — 22 citations into it; #18,632 of 21,575 by trust here, #19,310 by citations
• Recommender Systems — 16 citations into it
• Management Science and Operations Research — 11 citations into it
• Natural Language Processing — 8 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Marketing — 7 citations into it

Whom Ke Wang trusts overall

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

1. Geoffrey E. Hinton
2. Yoon Kim
3. Diederik P. Kingma
4. Ruslan Salakhutdinov
5. Steffen Rendle
6. Jimmy Ba
7. Alex Krizhevsky
8. Yoshua Bengio
9. Ilya Sutskever
10. Ruining He

Who trusts Ke Wang overall

1. Yupeng Hou
2. Fajie Yuan
3. Jiacheng Li
4. Kun Zhou
5. Jiaxi Tang
6. Julian McAuley
7. Xiangnan He
8. Xu Chen
9. Wang-Cheng Kang
10. Aminu Da’u

Papers from Ke Wang's perspective

Ordered by how strongly the researchers Ke Wang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding (2018) — 2,242 citations
• Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System (2018) — 231 citations