Cheng Tai

Optimization & Training · 2015

A researcher in the Science corpus: 2 papers; trusts 45 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 30 citations into it; #1,362 of 2,601 by trust here, #1,571 by citations
• Artificial Intelligence — 27 citations into it; #8,861 of 35,345 by trust here, #8,210 by citations
• Computer Vision and Pattern Recognition — 16 citations into it; #8,790 of 21,575 by trust here, #7,657 by citations
• Computational Mechanics — 14 citations into it
• Statistics and Probability — 6 citations into it; #5,174 of 12,932 by trust here, #4,253 by citations

Whom Cheng Tai trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Ilya Sutskever
6. Yoshua Bengio
7. Tom Schaul
8. Christian Szegedy
9. Boris Polyak
10. Andrew Zisserman

Who trusts Cheng Tai overall

1. Wujie Wen
2. Yu Cheng
3. Yang He
4. Min Wang
5. Yerlan Idelbayev
6. Haichuan Yang
7. Jean Kossaifi
8. Elad Hoffer
9. Simon Vandenhende
10. Xin Dong

Papers from Cheng Tai's perspective

Ordered by how strongly the researchers Cheng Tai 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Convolutional neural networks with low-rank regularization (2015) — 494 citations
• Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms (2015) — 337 citations