Chong You

Computer Vision and Pattern Recognition · with Ma · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 150 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 81 citations into it; #19,706 of 21,575 by trust here, #14,822 by citations
• Artificial Intelligence — 66 citations into it; #29,940 of 35,345 by trust here, #24,417 by citations
• Model Architectures — 26 citations into it
• Representation & Self-Supervised Learning — 25 citations into it
• Computational Mechanics — 24 citations into it
• Signal Processing — 15 citations into it
• Optimization & Training — 13 citations into it
• Statistical and Nonlinear Physics — 6 citations into it

Whom Chong You trusts overall

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

1. René Vidal
2. Ehsan Elhamifar
3. Yann LeCun
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Kaiming He
8. Joan Bruna
9. L. Eon Bottou
10. Guangcan Liu

Who trusts Chong You overall

1. Zhiyuan Dang
2. Bo Yang
3. Pan Ji
4. Kyungho Baek
5. Zhao Kang
6. Cheng Deng
7. Xiao Fu
8. T. Zhang
9. Wangtao Zhou

Papers from Chong You's perspective

Ordered by how strongly the researchers Chong You 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit (2015) — 379 citations
• Deep Networks from the Principle of Rate Reduction (2020) — 22 citations
• Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020) — 251 citations
• Incremental Learning via Rate Reduction (2020) — 51 citations