Yuekai Sun
Statistics and Probability · 2012–2020
A researcher in the Science corpus: 9 papers; trusts 56 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 66 citations into it; #4,900 of 12,932 by trust here, #2,407 by citations
- Artificial Intelligence — 58 citations into it; #19,593 of 35,345 by trust here, #9,641 by citations
- Optimization & Training — 29 citations into it; #1,676 of 2,601 by trust here, #1,120 by citations
- Computational Mechanics — 28 citations into it; #3,389 of 10,001 by trust here, #3,908 by citations
- Statistical Learning Theory — 23 citations into it
- Computer Networks and Communications — 17 citations into it
- Safety, Robustness & Interpretability — 14 citations into it
- Computer Vision and Pattern Recognition — 12 citations into it
Whom Yuekai Sun trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- Trevor J. Hastie
- Yurii E. Nesterov
- Martin J. Wainwright
- Jerome H. Friedman
- Roman Vershynin
- Hui Zou
- Adel Javanmard
- Yoav Benjamini
- Michael Patriksson
Who trusts Yuekai Sun overall
- Robert Tibshirani
- Xiang Li
- Jonathan E. Taylor
- William Fithian
- Qinbin Li
- Stefan Wager
- Chaoyang He
- Jialei Wang
- Yuchen Zhang
- Dmitrii Ostrovskii
Papers from Yuekai Sun's perspective
Ordered by how strongly the researchers Yuekai Sun trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Regression Shrinkage and Selection via the Lasso
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Federated Learning with Matched Averaging (2020) — 1,404 citations
- Exact post-selection inference, with application to the lasso (2013) — 811 citations
- Communication-efficient sparse regression: a one-shot approach (2015) — 70 citations
- Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0 (2019) — 1,031 citations
- Debiasing representations by removing unwanted variation due to protected attributes (2018) — 12 citations
- Communication-efficient Sparse Regression (2017) — 193 citations
- On conditional parity as a notion of non-discrimination in machine learning (2017) — 40 citations
- Exact post-selection inference with the lasso (2013) — 86 citations
- Proximal Newton-Type Methods for Minimizing Composite Functions (2012) — 340 citations