Yuxin Chen
Computational Mechanics · with Chi · 2015–2020
A researcher in the Science corpus: 6 papers; trusts 99 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 111 citations into it; #7,181 of 10,001 by trust here, #3,763 by citations
- Artificial Intelligence — 63 citations into it; #9,881 of 35,345 by trust here, #19,018 by citations
- Computer Vision and Pattern Recognition — 55 citations into it
- Statistics and Probability — 43 citations into it; #3,576 of 12,932 by trust here, #5,481 by citations
- Optimization & Training — 40 citations into it; #762 of 2,601 by trust here, #1,083 by citations
- Statistical Learning Theory — 31 citations into it; #994 of 1,038 by trust here, #836 by citations
- Radiation — 29 citations into it; #295 of 407 by trust here, #250 by citations
- Signal Processing — 25 citations into it
Whom Yuxin Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- Prateek Jain
- Praneeth Netrapalli
- Joel A. Tropp
- Yurii E. Nesterov
- Veit Elser
- Ruoyu Sun
- Sébastien Bubeck
- David R. Hunter
- Sujay Sanghavi
Who trusts Yuxin Chen overall
- Yuejie Chi
- Cong Ma
- Pinhan Chen
- Tom Goldstein
- Ju Sun
- Sharan Vaswani
- G. Wang
- Yue M. Lu
- Heejong Bong
- Kaizheng Wang
Papers from Yuxin Chen's perspective
Ordered by how strongly the researchers Yuxin Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems (2015) — 623 citations
- Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview (2018) — 491 citations
- Spectral Method and Regularized MLE Are Both Optimal for Top-$K$ Ranking (2017) — 130 citations
- Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction (2020) — 145 citations
- Nonconvex Low-Rank Tensor Completion from Noisy Data (2019) — 95 citations
- Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution (2017) — 265 citations