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Papers
A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation
JMLR 2026
Nonparametric Estimation of a Factorizable Density using Diffusion Models
JMLR 2026
Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention
ALT 2026
Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal
ICML 2025
Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
ICML 2025
On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension
JMLR 2025
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
ICLR 2025
Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights
JMLR 2025
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees
ICLR 2025
Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design
JMLR 2024
Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable
AISTATS 2024
Non-parametric classification via expand-and-sparsify representation
NeurIPS 2024
Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks
JMLR 2024
On The Statistical Complexity of Offline Decision-Making
ICML 2024
Statistical Spatially Inhomogeneous Diffusion Inference
AAAI 2024
Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
ICML 2024
The Aggregation–Heterogeneity Trade-off in Federated Learning
COLT 2023
The Exact Sample Complexity Gain from Invariances for Kernel Regression
NeurIPS 2023
Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models
JMLR 2023
A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation
ICML 2022
A NON-PARAMETRIC REGRESSION VIEWPOINT : GENERALIZATION OF OVERPARAMETRIZED DEEP RELU NETWORK UNDER NOISY OBSERVATIONS
ICLR 2022
Asymptotic Properties for Bayesian Neural Network in Besov Space
NeurIPS 2022
On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation
ICML 2022
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism
NeurIPS 2021
Learning Strategies in Decentralized Matching Markets under Uncertain Preferences
JMLR 2021