Zenglin Xu

Artificial Intelligence · 2009–2021

A researcher in the Science corpus: 5 papers; trusts 502 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 170 citations into it; #30,677 of 35,345 by trust here, #17,776 by citations
• Computer Vision and Pattern Recognition — 143 citations into it; #18,806 of 21,575 by trust here, #12,992 by citations
• Representation & Self-Supervised Learning — 81 citations into it
• Natural Language Processing — 37 citations into it
• Optimization & Training — 22 citations into it
• Evaluation & Benchmarks — 20 citations into it
• Generative Models — 20 citations into it
• Graph Learning — 18 citations into it

Whom Zenglin Xu trusts overall

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

1. Francis R. Bach
2. Geoffrey E. Hinton
3. Thorsten Joachims
4. Yoshua Bengio
5. Alex Krizhevsky
6. Andrew Y. Ng
7. Diederik P. Kingma
8. Yann LeCun
9. Kaiming He
10. Gert R. G. Lanckriet

Who trusts Zenglin Xu overall

1. Girish Chandrashekar
2. Jakramate Bootkrajang
3. Xiao-Lei Zhang
4. Nan Du
5. Zheng Zhao
6. Jie Cai
7. Tianbao Yang
8. Rong Jin
9. Ferat Sahin
10. Ata Kabán

Papers from Zenglin Xu's perspective

Ordered by how strongly the researchers Zenglin Xu 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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

• A Survey on Deep Semi-Supervised Learning (2021) — 910 citations
• Large-scale Multi-view Subspace Clustering in Linear Time (2019) — 602 citations
• Superneurons: dynamic GPU memory management for training deep neural networks (2018) — 294 citations
• Simple and Efficient Multiple Kernel Learning by Group Lasso (2010) — 294 citations
• Discriminative Semi-Supervised Feature Selection Via Manifold Regularization (2009) — 376 citations