Yuejie Chi
Computational Mechanics · 2010–2020
A researcher in the Science corpus: 5 papers; trusts 108 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 119 citations into it; #4,500 of 10,001 by trust here, #2,644 by citations
- Artificial Intelligence — 68 citations into it; #28,166 of 35,345 by trust here, #31,361 by citations
- Computer Vision and Pattern Recognition — 41 citations into it; #16,688 of 21,575 by trust here, #15,162 by citations
- Optimization & Training — 38 citations into it; #2,173 of 2,601 by trust here, #1,661 by citations
- Statistics and Probability — 36 citations into it
- Statistical Learning Theory — 26 citations into it; #993 of 1,038 by trust here, #836 by citations
- Signal Processing — 25 citations into it; #6,009 of 7,572 by trust here, #7,486 by citations
- Biomedical Engineering — 23 citations into it; #6,966 of 10,734 by trust here, #7,436 by citations
Whom Yuejie Chi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- Yurii E. Nesterov
- Prateek Jain
- Rong Ge
- Bin Yang
- B. Recht
- Yuxin Chen
- Raghunandan H. Keshavan
- Praneeth Netrapalli
- Roman Vershynin
Who trusts Yuejie Chi overall
- E.J. Candes
- Bo Li
- Hao Zhu
- Athina P. Petropulu
- Badri Narayan Bhaskar
- Carlos Fernandez-Granda
- Marco F. Duarte
- Liangzu Peng
- Gongguo Tang
- Geert Leus
Papers from Yuejie Chi's perspective
Ordered by how strongly the researchers Yuejie Chi 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
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- 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
- Sensitivity to Basis Mismatch in Compressed Sensing (2010) — 981 citations
- Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview (2018) — 491 citations
- Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction (2020) — 145 citations
- Streaming PCA and Subspace Tracking: The Missing Data Case (2018) — 101 citations
- Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution (2017) — 265 citations