Guang Cheng

Jordan Awan

J. Mach. Learn. Res., 2025

Decentralized Sparse Linear Regression via Gradient-Tracking.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2025

Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2025

CTSyn: A Foundation Model for Cross Tabular Data Generation.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

Ensembling Membership Inference Attacks Against Tabular Generative Models.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM Workshop on Artificial Intelligence and Security, 2025

2024

Watermarking Generative Categorical Data.

[BibT_eX]

[DOI]

Bochao Gu

Hengzhi He

CoRR, 2024

TimeAutoDiff: Combining Autoencoder and Diffusion model for time series tabular data synthesizing.

[BibT_eX]

[DOI]

CoRR, 2024

Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data.

[BibT_eX]

[DOI]

CoRR, 2024

Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Models.

[BibT_eX]

[DOI]

Joshua Ward

CoRR, 2024

CTSyn: A Foundational Model for Cross Tabular Data Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Dynamic Online Recommendation for Two-Sided Market with Bayesian Incentive Compatibility.

[BibT_eX]

[DOI]

Xiaowu Dai

CoRR, 2024

Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space.

[BibT_eX]

[DOI]

CoRR, 2024

BadGD: A unified data-centric framework to identify gradient descent vulnerabilities.

[BibT_eX]

[DOI]

CoRR, 2024

Discriminative Estimation of Total Variation Distance: A Fidelity Auditor for Generative Data.

[BibT_eX]

[DOI]

CoRR, 2024

Watermarking Generative Tabular Data.

[BibT_eX]

[DOI]

CoRR, 2024

Approximation of RKHS Functionals by Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Rate-Optimal Rank Aggregation with Private Pairwise Rankings.

[BibT_eX]

[DOI]

Shirong Xu

Will Wei Sun

CoRR, 2024

Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data.

[BibT_eX]

[DOI]

CoRR, 2024

A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models.

[BibT_eX]

[DOI]

Namjoon Suh

CoRR, 2024

Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models.

[BibT_eX]

[DOI]

CoRR, 2024

Improve Fidelity and Utility of Synthetic Credit Card Transaction Time Series from Data-centric Perspective.

[BibT_eX]

[DOI]

Din-Yin Hsieh

CoRR, 2024

Transfer Learning for Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints.

[BibT_eX]

[DOI]

Xiaowu Dai

Proceedings of the Forty-first International Conference on Machine Learning, 2024

FairRR: Pre-Processing for Group Fairness through Randomized Response.

[BibT_eX]

[DOI]

Joshua John Ward

Xianli Zeng

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Binary Classification under Local Label Differential Privacy Using Randomized Response Mechanisms.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Optimal Convergence Rates of Deep Convolutional Neural Networks: Additive Ridge Functions.

[BibT_eX]

[DOI]

Zhiying Fang

Trans. Mach. Learn. Res., 2023

AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizing.

[BibT_eX]

[DOI]

CoRR, 2023

MissDiff: Training Diffusion Models on Tabular Data with Missing Values.

[BibT_eX]

[DOI]

CoRR, 2023

Utility Theory of Synthetic Data Generation.

[BibT_eX]

[DOI]

Shirong Xu

Will Wei Sun

CoRR, 2023

Double Matching Under Complementary Preferences.

[BibT_eX]

[DOI]

Xiaowu Dai

CoRR, 2023

Ranking Differential Privacy.

[BibT_eX]

[DOI]

Shirong Xu

Will Wei Sun

CoRR, 2023

Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process.

[BibT_eX]

[DOI]

Yidong Ouyang

Liyan Xie

Proceedings of the International Conference on Machine Learning, 2023

Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms.

[BibT_eX]

[DOI]

Ximing Li

Chendi Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Benefit of Interpolation in Nearest Neighbor Algorithms.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., June, 2022

Variance reduction on general adaptive stochastic mirror descent.

[BibT_eX]

[DOI]

Mach. Learn., 2022

Distributed Bootstrap for Simultaneous Inference Under High Dimensionality.

[BibT_eX]

[DOI]

Yang Yu

Shih-Kang Chao

J. Mach. Learn. Res., 2022

On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation.

[BibT_eX]

[DOI]

Yucong Liu

CoRR, 2022

Improving Adversarial Robustness by Contrastive Guided Diffusion Process.

[BibT_eX]

[DOI]

Yidong Ouyang

Liyan Xie

CoRR, 2022

Rate-Optimal Contextual Online Matching Bandit.

[BibT_eX]

[DOI]

CoRR, 2022

Enhanced Nearest Neighbor Classification for Crowdsourcing.

[BibT_eX]

[DOI]

Jiexin Duan

CoRR, 2022

Attention Enables Zero Approximation Error.

[BibT_eX]

[DOI]

CoRR, 2022

Optimal Learning Rates of Deep Convolutional Neural Networks: Additive Ridge Functions.

[BibT_eX]

[DOI]

Zhiying Fang

CoRR, 2022

High-Dimensional Inference over Networks: Linear Convergence and Statistical Guarantees.

[BibT_eX]

[DOI]

CoRR, 2022

Residual bootstrap exploration for stochastic linear bandit.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Phase Transition from Clean Training to Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Why Do Artificially Generated Data Help Adversarial Robustness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unlabeled Data Help: Minimax Analysis and Adversarial Robustness.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Optimum-statistical collaboration towards efficient black-box optimization.

[BibT_eX]

[DOI]

Wenjie Li

CoRR, 2021

On the Algorithmic Stability of Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarially Robust Estimate and Risk Analysis in Linear Regression.

[BibT_eX]

[DOI]

Ruizhi Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On the Generalization Properties of Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Online Forgetting Process for Linear Regression Models.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Tensor Graphical Model: Non-Convex Optimization and Statistical Inference.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Variance Reduction on Adaptive Stochastic Mirror Descent.

[BibT_eX]

[DOI]

CoRR, 2020

Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors.

[BibT_eX]

[DOI]

Jincheng Bai

CoRR, 2020

Online Regularization for High-Dimensional Dynamic Pricing Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

On Deep Instrumental Variables Estimate.

[BibT_eX]

[DOI]

Ruiqi Liu

CoRR, 2020

Residual Bootstrap Exploration for Bandit Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting.

[BibT_eX]

[DOI]

Tianyang Hu

CoRR, 2020

Statistical Guarantees of Distributed Nearest Neighbor Classification.

[BibT_eX]

[DOI]

Jiexin Duan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Directional Pruning of Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee.

[BibT_eX]

[DOI]

Jincheng Bai

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Simultaneous Inference for Massive Data: Distributed Bootstrap.

[BibT_eX]

[DOI]

Yang Yu

Shih-Kang Chao

Proceedings of the 37th International Conference on Machine Learning, 2020

Mutual Transfer Learning for Massive Data.

[BibT_eX]

[DOI]

Ching-Wei Cheng

Proceedings of the 37th International Conference on Machine Learning, 2020

Non-asymptotic Analysis for Nonparametric Testing.

[BibT_eX]

[DOI]

Yun Yang

Proceedings of the Conference on Learning Theory, 2020

Online Batch Decision-Making with High-Dimensional Covariates.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Sparse and Low-rank Tensor Estimation via Cubic Sketchings.

[BibT_eX]

[DOI]

Botao Hao

Anru R. Zhang

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Nonparametric Bayesian Aggregation for Massive Data.

[BibT_eX]

[DOI]

Botao Hao

J. Mach. Learn. Res., 2019

A generalization of regularized dual averaging and its dynamics.

[BibT_eX]

[DOI]

Shih-Kang Chao

CoRR, 2019

Rates of Convergence for Large-scale Nearest Neighbor Classification.

[BibT_eX]

[DOI]

Jiexin Duan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bootstrapping Upper Confidence Bound.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sharp Theoretical Analysis for Nonparametric Testing under Random Projection.

[BibT_eX]

[DOI]

Meimei Liu

Proceedings of the Conference on Learning Theory, 2019

2018

Stein Neural Sampler.

[BibT_eX]

[DOI]

CoRR, 2018

Statistical Optimality of Interpolated Nearest Neighbor Algorithms.

[BibT_eX]

[DOI]

CoRR, 2018

Early Stopping for Nonparametric Testing.

[BibT_eX]

[DOI]

Meimei Liu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data.

[BibT_eX]

[DOI]

Ganggang Xu

Proceedings of the 35th International Conference on Machine Learning, 2018

Statistically and Computationally Efficient Variance Estimator for Kernel Ridge Regression.

[BibT_eX]

[DOI]

Meimei Liu

Jean Honorio

Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017

Computational Limits of A Distributed Algorithm for Smoothing Spline.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

Simultaneous Clustering and Estimation of Heterogeneous Graphical Models.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

2016

Analysing the Semantic Change Based on Word Embedding.

[BibT_eX]

[DOI]

Xuanyi Liao

Proceedings of the Natural Language Understanding and Intelligent Applications, 2016

2015

Non-convex Statistical Optimization for Sparse Tensor Graphical Model.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Nearest Neighbor Classifier with Optimal Stability.

[BibT_eX]

[DOI]

Wei Sun