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Limiting empirical spectral distribution for products of rectangular matrices

Yongcheng Qi, and Hongru Zhao. Journal of Mathematical Analysis and Applications 502, no. 2 (2021): 125237.
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Exponential stability of the linear KdV-BBM equation

Kangsheng Liu, Zhuangyi Liu, and Hongru Zhao. Discrete and Continuous Dynamical Systems-B 29, no. 3 (2024): 1206-1216.
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Convergence Analysis and Trajectory Comparison of Gradient Descent for Overparameterized Deep Linear Networks

Hongru Zhao, Jinchao Xu. Transactions on Machine Learning Research (2024)
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Distributed Algorithms for High-Dimensional Statistical Inference and Structure Learning with Heterogeneous Data

Hongru Zhao, and Xiaotong Shen. (2025) Statistica Sinica (forthcoming).
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Subspace Decompositions for Association Structure Learning in Multivariate Categorical Response Regression

Hongru Zhao, Aaron J. Molstad, and Adam J. Rothman. Preprint (2025)
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Globally-Optimal Greedy Active Sequential Estimation

Xiaoou Li, and Hongru Zhao. IEEE Transactions on Information Theory 71, no. 5 (2025): 3871–3924.
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Allocation-Constrained Adaptive Design and Sequential Estimation: Theory and Application to Bradley–Terry–Davidson Models

Hongru Zhao. Submitted, Journal of Statistical Planning and Inference (2025).

On Validating Angular Power Spectral Models for the Stochastic Gravitational-Wave Background Without Distributional Assumptions

Xiangyu Zhang, Erik Floden, Hongru Zhao, Sara Algeri, Galin Jones, Vuk Mandic, and Jesse Miller. (2025) Physical Review D (forthcoming).
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Testing models for angular power spectra: A distribution-free approach

Sara Algeri, Xiangyu Zhang, Erik Floden, Hongru Zhao, Galin L. Jones, Vuk Mandic, and Jesse Miller. (2025) Physical Review D (forthcoming).
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Convergence and Stability Analysis of Self-Consuming Generative Models with Heterogeneous Human Curation

Hongru Zhao, Jinwen Fu, and Tuan Pham. Preprint.
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Talk on Convergence Analysis and Trajectory Comparison of Gradient Descent for Overparameterized Deep Linear Networks

Poster Presentation on Learning Association Structures via Subspace Decomposition in Multivariate Categorical Response Regression

Contributed Paper Presentation on Subspace Decompositions for Association Structure Learning in Multivariate Categorical Response Regression

STAT 3011 - Intro Statistical Analysis

Undergraduate course, UMN, School of Statistics, 2023

STAT 3301 - Regression and Statistical Computing

Undergraduate course, UMN, School of Statistics, 2024

STAT 4101 - Theory of Statistics I

Undergraduate course, UMN, School of Statistics, 2024

STAT 3301 - Regression and Statistical Computing

Undergraduate course, UMN, School of Statistics, 2025

STAT 4102 - Theory of Statistics II

Undergraduate course, UMN, School of Statistics, 2025

STAT 4052 - Statistical Machine Learning II

Undergraduate course, UMN, School of Statistics, 2026