Tuo Zhao

发表

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks

Wenjing Liao, Yao Xie, Jie Wang, 2022, 2205.02043.

Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks

Mengdi Wang, Minshuo Chen, Tuo Zhao, 2022, ArXiv.

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint

Wenjing Liao, Minshuo Chen, Hao Liu, 2022, ICML.

First-order Policy Optimization for Robust Markov Decision Process

Guanghui Lan, Yan Li, Tuo Zhao, 2022, ArXiv.

Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks

Mengdi Wang, Minshuo Chen, Tuo Zhao, 2022, ICLR.

High dimensional binary classification under label shift: phase transition and regularization

Wenjing Liao, Minshuo Chen, Hao Liu, 2022, Sampling Theory, Signal Processing, and Data Analysis.

Toward Understanding the Importance of Noise in Training Neural Networks

Tuo Zhao, Enlu Zhou, Tianyi Liu, 2019, ICML.

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds

Wenjing Liao, Minshuo Chen, Tuo Zhao, 2023, NeurIPS.

Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data

Mengdi Wang, Minshuo Chen, Tuo Zhao, 2023, ICML.

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Alexander W. Bukharin, Weizhu Chen, Pengcheng He, 2023, ICLR.

First-order Policy Optimization for Robust Markov Decision Process

Guanghui Lan, Yan Li, Tuo Zhao, 2022, ArXiv.

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks

Wenjing Liao, Yao Xie, Minshuo Chen, 2022, Information and Inference: A Journal of the IMA.

Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably

Enlu Zhou, Tianyi Liu, Yan Li, 2022, AISTATS.

Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks

H. Zha, Wenjing Liao, Minshuo Chen, 2020, 2002.03938.

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks

Yu-Xiang Wang, Mengdi Wang, Minshuo Chen, 2023, ArXiv.

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories

Mengdi Wang, Wenjing Liao, Minshuo Chen, 2023, ICML.

Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems

Mengdi Wang, Minshuo Chen, Tuo Zhao, 2023, ArXiv.