Ming Yin

Computer Vision and Pattern Recognition · with Gao

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Computational Mechanics — 15 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Artificial Intelligence — 7 citations into it

Whom Ming Yin trusts overall

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

1. E.J. Candes
2. A. Hinge
3. Mikhail Belkin
4. Zhouchen Lin
5. Shuicheng Yan
6. Yi Ma
7. Jian-Feng Cai
8. John Wright
9. Partha Niyogi
10. Minming Chen

Who trusts Ming Yin overall

1. Hongyun Cai
2. Mengyue Geng
3. Yang Wang
4. Vincent Wenchen Zheng
5. Yaowei Wang
6. Lin Wu

Papers from Ming Yin's perspective

Ordered by how strongly the researchers Ming Yin 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Ieee Transactions on Pattern Analysis and Machine Intelligence Laplacian Regularized Low-rank Representation and Its Applications