Heteroskedastic Tensor Clustering Yuchen Zhou, Yuxin Chen Under revision
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA Yuchen Zhou, Yuxin Chen Accepted to Annals of Statistics
Inference for Low-rank Tensors – No Need to Debias Dong Xia, Anru Zhang, Yuchen Zhou (alphabetical order) Annals of Statistics, 2022
Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration Yuchen Zhou, Anru Zhang, Lili Zheng, Yazhen Wang IEEE Transactions on Information Theory, 2022 (This paper received IMS Hannan Graduate Student Travel Award, 2021.)
Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference T. Tony Cai, Anru Zhang, Yuchen Zhou (alphabetical order) IEEE Transactions on Information Theory, 2022
High-dimensional Log-Error-in-Variable Regression with Applications to Microbial Compositional Data Analysis Pixu Shi, Yuchen Zhou, Anru Zhang (: equal contributions) Biometrika, 2022 (This paper received Biometrics Early-Stage Investigator Award by the Biometrics Section of the American Statistical Association, 2019.)
On the Non-asymptotic and Sharp Lower Tail Bounds of Random Variables Anru Zhang, Yuchen Zhou (alphabetical order) STAT, 2020
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar (: equal contributions) Advances in Neural Information Processing Systems (NeurIPS), 2019
Dropout Training, Data-dependent Regularization, and Generalization Bounds Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang International Conference on Machine Learning (ICML), 2018
Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations Chen Dan, Kristoffer Arnsfelt Hansen, He Jiang, Liwei Wang, Yuchen Zhou (alphabetical order) 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS), 2018