activity
20242026
most citedWhich exceptional low-dimensional projections of a Gaussian point cloud can be found in polynomial time?

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

math.ST2026

Efficient and Adaptive Estimation of Portfolio Weights with Spectral Risk Measures

Kangjie Zhou, Ming Yuan

Spectral risk measures, including conditional value-at-risk (CVaR), generate a family of convex criteria for portfolio estimation. We study how the criterion should be chosen when…

math.ST2025

Basic Inequalities for First-Order Optimization with Applications to Statistical Risk Analysis

Seunghoon Paik, Kangjie Zhou, Matus Telgarsky +1

In this work, we introduce for first-order iterative optimization algorithms, forming a simple yet versatile framework which connects implicit and exp…

math.ST2025

A statistical theory of overfitting for imbalanced classification

Jingyang Lyu, Kangjie Zhou, Yiqiao Zhong

Classification with imbalanced data is a common challenge in data analysis, where certain classes (minority classes) account for a small fraction of the training data compared with…

cs.LG2025

Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks

Yuhang Cai, Kangjie Zhou, Jingfeng Wu +3

We establish the asymptotic implicit bias of gradient descent (GD) for generic non-homogeneous deep networks under exponential loss. Specifically, we characterize three key propert…

math.PR2024★ 1 cited

Which exceptional low-dimensional projections of a Gaussian point cloud can be found in polynomial time?

Andrea Montanari, Kangjie Zhou

Given -dimensional standard Gaussian vectors , we consider the set of all empirical distributions of its -dimensional projections, f…

stat.ME2024

Dynamic Factor Analysis of High-dimensional Recurrent Events

Fangyi Chen, Yunxiao Chen, Zhiliang Ying +1

Recurrent event time data arise in many studies, including biomedicine, public health, marketing, and social media analysis. High-dimensional recurrent event data involving many ev…

cs.LG2024

Sharp Analysis of Power Iteration for Tensor PCA

Yuchen Wu, Kangjie Zhou

We investigate the power iteration algorithm for the tensor PCA model introduced in Richard and Montanari (2014). Previous work studying the properties of tensor power iteration is…