Publications (26)
Third-order Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima
Yaodong Yu, Pan Xu, Quanquan Gu
Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently
Yaodong Yu, Difan Zou, Quanquan Gu
An Improved Analysis of Training Over-parameterized Deep Neural Networks
Difan Zou, Quanquan Gu
Stochastic Variance-Reduced Cubic Regularized Newton Method
Dongruo Zhou, Pan Xu, Quanquan Gu
Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation
Huan Gui, Quanquan Gu
Local and Global Inference for High Dimensional Nonparanormal Graphical Models
Quanquan Gu, Yuan Cao, Yang Ning +1
Sharp Computational-Statistical Phase Transitions via Oracle Computational Model
Zhaoran Wang, Quanquan Gu, Han Liu
Generalized Fisher Score for Feature Selection
Quanquan Gu, Zhenhui Li, Jiawei Han
An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient
Pan Xu, Felicia Gao, Quanquan Gu
Stochastic Variance-reduced Gradient Descent for Low-rank Matrix Recovery from Linear Measurements
Xiao Zhang, Lingxiao Wang, Quanquan Gu
High Dimensional Expectation-Maximization Algorithm: Statistical Optimization and Asymptotic Normality
Zhaoran Wang, Quanquan Gu, Yang Ning +1
A Unified Computational and Statistical Framework for Nonconvex Low-Rank Matrix Estimation
Lingxiao Wang, Xiao Zhang, Quanquan Gu
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks
Difan Zou, Yuan Cao, Dongruo Zhou +1
Communication-efficient Distributed Estimation and Inference for Transelliptical Graphical Models
Pan Xu, Lu Tian, Quanquan Gu
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang, Simon S. Du, Quanquan Gu
Communication-efficient Distributed Sparse Linear Discriminant Analysis
Lu Tian, Quanquan Gu
Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
Dongruo Zhou, Quanquan Gu
A Unified Framework for Low-Rank plus Sparse Matrix Recovery
Xiao Zhang, Lingxiao Wang, Quanquan Gu
High Dimensional Multivariate Regression and Precision Matrix Estimation via Nonconvex Optimization
Jinghui Chen, Quanquan Gu
Finding Local Minima via Stochastic Nested Variance Reduction
Dongruo Zhou, Pan Xu, Quanquan Gu
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations
Pan Xu, Jian Ma, Quanquan Gu
Statistical Limits of Convex Relaxations
Zhaoran Wang, Quanquan Gu, Han Liu
Sample Efficient Stochastic Variance-Reduced Cubic Regularization Method
Dongruo Zhou, Pan Xu, Quanquan Gu
Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption
Jinghui Chen, Lingxiao Wang, Xiao Zhang +1
A Universal Variance Reduction-Based Catalyst for Nonconvex Low-Rank Matrix Recovery
Lingxiao Wang, Xiao Zhang, Quanquan Gu
Learning One-hidden-layer ReLU Networks via Gradient Descent
Xiao Zhang, Yaodong Yu, Lingxiao Wang +1