Hybrid regularization image deblurring in the presence of impulsive noise. - Fenge Chen; Yuling Jiao; Guorui Ma; Qianqing Qin (J. Vis. Commun. Image Represent., 2013)

A Primal Dual Active Set with Continuation Algorithm for the ell^0-Regularized Optimization Problem. - Yuling Jiao; Bangti Jin; Xiliang Lu (CoRR, 2014)

Image Deblurring Via Combined Total Variation and Framelet. - Fenge Chen; Yuling Jiao; Liyu Lin; Qianqing Qin (Circuits Syst. Signal Process., 2014)

A Primal Dual Active Set Algorithm With Continuation for Compressed Sensing. - Qibin Fan; Yuling Jiao; Xiliang Lu (IEEE Trans. Signal Process., 2014)

Numerical identification of a sparse Robin coefficient. - Zhiyuan Sun; Yuling Jiao; Bangti Jin; Xiliang Lu (Adv. Comput. Math., 2015)

A multi-parameter regularization model for image restoration. - Qibin Fan; Dandan Jiang; Yuling Jiao (Signal Process., 2015)

An Alternating Direction Method with Continuation for Nonconvex Low Rank Minimization. - Zheng-Fen Jin; Zhongping Wan; Yuling Jiao; Xiliang Lu (J. Sci. Comput., 2016)

Alternating Direction Method of Multipliers for Linear Inverse Problems. - Yuling Jiao; Qinian Jin; Xiliang Lu; Weijie Wang (SIAM J. Numer. Anal., 2016)

Stripe Noise Separation and Removal in Remote Sensing Images by Consideration of the Global Sparsity and Local Variational Properties. - Xinxin Liu 002; Xiliang Lu; Huanfeng Shen; Qiangqiang Yuan; Yuling Jiao; Liangpei Zhang 001 (IEEE Trans. Geosci. Remote. Sens., 2016)

A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression. - Yongxiu Cao; Jian Huang 003; Yuling Jiao; Yanyan Liu (Commun. Stat. Simul. Comput., 2017)

Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery. - Yuling Jiao; Bangti Jin; Xiliang Lu (IEEE Signal Process. Lett., 2017)

Group Sparse Recovery via the ℓ0(ℓ2) Penalty: Theory and Algorithm. - Yuling Jiao; Bangti Jin; Xiliang Lu (IEEE Trans. Signal Process., 2017)

SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties. - Jian Huang 003; Yuling Jiao; Xiliang Lu; Yueyong Shi; Qinglong Yang (CoRR, 2018)

A Constructive Approach to $L_0$ Penalized Regression. - Jian Huang 003; Yuling Jiao; Yanyan Liu; Xiliang Lu (J. Mach. Learn. Res., 2018)

Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares. - Jian Huang 003; Yuling Jiao; Xiliang Lu; Liping Zhu (SIAM J. Sci. Comput., 2018)

Deep Generative Learning via Variational Gradient Flow. - Yuan Gao 044; Yuling Jiao; Yang Wang; Yao Wang 003; Can Yang 002; Shunkang Zhang (ICML, 2019)

VIMCO: variational inference for multiple correlated outcomes in genome-wide association studies. - Xingjie Shi; Yuling Jiao; Yi Yang 028; Ching-Yu Cheng; Can Yang 002; Xinyi Lin; Jin Liu 011 (Bioinform., 2019)

Wasserstein-Wasserstein Auto-Encoders. - Shunkang Zhang; Yuan Gao 044; Yuling Jiao; Jin Liu 011; Yang Wang; Can Yang 002 (CoRR, 2019)

A stochastic alternating minimizing method for sparse phase retrieval. - Jianfeng Cai 001; Yuling Jiao; Xiliang Lu; Juntao You (CoRR, 2019)

Variable Selection via Generalized SELO-Penalized Cox Regression Models. - Yueyong Shi; Deyi Xu; Yongxiu Cao; Yuling Jiao (J. Syst. Sci. Complex., 2019)

A Nonconvex Model with Minimax Concave Penalty for Image Restoration. - Juntao You; Yuling Jiao; Xiliang Lu; Tieyong Zeng (J. Sci. Comput., 2019)

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies. - Yi Yang 028; Xingjie Shi; Yuling Jiao; Jian Huang 003; Min Chen; Xiang Zhou; Lei Sun; Xinyi Lin; Can Yang 002; Jin Liu 011 (Bioinform., 2020)

A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models. - Jian Huang 003; Yuling Jiao; Lican Kang; Jin Liu 011; Yanyan Liu; Xiliang Lu (CoRR, 2020)

Learning Implicit Generative Models with Theoretical Guarantees. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011 (CoRR, 2020)

Robust Decoding from Binary Measurements with Cardinality Constraint Least Squares. - Zhao Ding; Junjun Huang; Yuling Jiao; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2020)

Generative Learning With Euler Particle Transport. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2020)

A Semismooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning. - Yueyong Shi; Jian Huang 003; Yuling Jiao; Qinglong Yang (IEEE Trans. Neural Networks Learn. Syst., 2020)

Deep Generative Learning via Schrödinger Bridge. - Gefei Wang; Yuling Jiao; Qian Xu; Yang Wang 020; Can Yang (ICML, 2021)

Deep Generative Learning via Euler Particle Transport. - Yuan Gao 044; Jian Huang 003; Yuling Jiao; Jin Liu 011; Xiliang Lu; Jerry Zhijian Yang (MSML, 2021)

Non-asymptotic Error Bounds for Bidirectional GANs. - Shiao Liu; Yunfei Yang 002; Jian Huang 003; Yuling Jiao; Yang Wang 020 (NeurIPS, 2021)

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class. - Yuling Jiao; Yanming Lai; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2021)

Convergence Rate Analysis for Deep Ritz Method. - Chenguang Duan; Yuling Jiao; Yanming Lai; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2021)

Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (CoRR, 2021)

Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity. - Yuling Jiao; Lican Kang; Yanyan Liu; Youzhou Zhou (CoRR, 2021)

Error Analysis of Deep Ritz Methods for Elliptic Equations. - Yuling Jiao; Yanming Lai; Yisu Luo; Yang Wang 020; Yunfei Yang 002 (CoRR, 2021)

Convergence Analysis for the PINNs. - Yuling Jiao; Yanming Lai; Dingwei Li; Xiliang Lu; Yang Wang; Jerry Zhijian Yang (CoRR, 2021)

Coordinate Descent for MCP/SCAD Penalized Least Squares Converges Linearly. - Yuling Jiao; Dingwei Li; Min Liu; Xiliang Lu (CoRR, 2021)

Relative Entropy Gradient Sampler for Unnormalized Distributions. - Xingdong Feng; Yuan Gao 044; Jian Huang 003; Yuling Jiao; Xu Liu 024 (CoRR, 2021)

Analysis of Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Conditions. - Chenguang Duan; Yuling Jiao; Yanming Lai; Xiliang Lu; Qimeng Quan; Jerry Zhijian Yang (CoRR, 2021)

Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension. - Yuling Jiao; Dingwei Li; Min Liu; Xiangliang Lu; Yuanyuan Yang (CoRR, 2021)

Wasserstein Generative Learning of Conditional Distribution. - Shiao Liu; Xingyu Zhou; Yuling Jiao; Jian Huang 003 (CoRR, 2021)

Fitting jump additive models. - Yicheng Kang; Yueyong Shi; Yuling Jiao; Wendong Li; Dongdong Xiang (Comput. Stat. Data Anal., 2021)

Distributed quantile regression for massive heterogeneous data. - Aijun Hu; Yuling Jiao; Yanyan Liu; Yueyong Shi; Yuanshan Wu (Neurocomputing, 2021)

Approximation with CNNs in Sobolev Space: with Applications to Classification. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (NeurIPS, 2022)

Approximation bounds for norm constrained neural networks with applications to regression and GANs. - Yuling Jiao; Yang Wang 020; Yunfei Yang 002 (CoRR, 2022)

Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning. - Qiuhao Chen; Yuxuan Du; Qi Zhao; Yuling Jiao; Xiliang Lu; Xingyao Wu (CoRR, 2022)

Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Joel L. Horowitz; Jian Huang 003 (CoRR, 2022)

ℓ0-Regularized high-dimensional accelerated failure time model. - Chao Cheng; Xingdong Feng; Jian Huang 003; Yuling Jiao; Shuang Zhang (Comput. Stat. Data Anal., 2022)

A data-driven line search rule for support recovery in high-dimensional data analysis. - Peili Li; Yuling Jiao; Xiliang Lu; Lican Kang (Comput. Stat. Data Anal., 2022)

GSDAR: a fast Newton algorithm for ℓ 0 regularized generalized linear models with statistical guarantee. - Jian Huang 003; Yuling Jiao; Lican Kang; Jin Liu 011; Yanyan Liu; Xiliang Lu (Comput. Stat., 2022)

An Error Analysis of Generative Adversarial Networks for Learning Distributions. - Jian Huang 003; Yuling Jiao; Zhen Li; Shiao Liu; Yang Wang 020; Yunfei Yang 002 (J. Mach. Learn. Res., 2022)

PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties. - Jian Huang 003; Yuling Jiao; Xiliang Lu; Yueyong Shi; Qinglong Yang; Yuanyuan Yang (Signal Process., 2022)

Sample-Efficient Sparse Phase Retrieval via Stochastic Alternating Minimization. - Jian-Feng Cai 001; Yuling Jiao; Xiliang Lu; Juntao You (IEEE Trans. Signal Process., 2022)

Fast Excess Risk Rates via Offset Rademacher Complexity. - Chenguang Duan; Yuling Jiao; Lican Kang; Xiliang Lu; Jerry Zhijian Yang (ICML, 2023)

Invariant and Sufficient Supervised Representation Learning. - Junyu Zhu; Xu Liao; Changshi Li; Yuling Jiao; Jin Liu 011; Xiliang Lu (IJCNN, 2023)

Convergence Analysis of the Deep Galerkin Method for Weak Solutions. - Yuling Jiao; Yanming Lai; Yang Wang 020; Haizhao Yang; Yunfei Yang 002 (CoRR, 2023)

GAS: A Gaussian Mixture Distribution-Based Adaptive Sampling Method for PINNs. - Yuling Jiao; Di Li; Xiliang Lu; Jerry Zhijian Yang; Cheng Yuan (CoRR, 2023)

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (CoRR, 2023)

Current density impedance imaging with PINNs. - Chenguang Duan; Yuling Jiao; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2023)

Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models. - Changyu Liu; Yuling Jiao; Junhui Wang; Jian Huang 003 (CoRR, 2023)

Provable Advantage of Parameterized Quantum Circuit in Function Approximation. - Zhan Yu; Qiuhao Chen; Yuling Jiao; Yinan Li; Xiliang Lu; Xin Wang; Jerry Zhijian Yang (CoRR, 2023)

Gaussian Interpolation Flows. - Yuan Gao; Jian Huang; Yuling Jiao (CoRR, 2023)

Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning. - Xingdong Feng; Yuling Jiao; Lican Kang; Baqun Zhang; Fan Zhou (J. Mach. Learn. Res., 2023)

PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. - Xinyi Yu; Jiashun Xiao; Mingxuan Cai; Yuling Jiao; Xiang Wan; Jin Liu 011; Can Yang 002 (Bioinform., 2023)

Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension. - Yuling Jiao; Dingwei Li; Min Liu; Xiliang Lu; Yuanyuan Yang (J. Sci. Comput., 2023)

Correction to: Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension. - Yuling Jiao; Dingwei Li; Min Liu; Xiliang Lu; Yuanyuan Yang (J. Sci. Comput., 2023)

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class. - Yuling Jiao; Yanming Lai; Xiliang Lu; Fengru Wang; Jerry Zhijian Yang; Yuanyuan Yang (SIAM J. Math. Anal., 2023)

Global Optimization via Schrödinger-Föllmer Diffusion. - Yin Dai; Yuling Jiao; Lican Kang; Xiliang Lu; Jerry Zhijian Yang (SIAM J. Control. Optim., 2023)

Neural Network Approximation for Pessimistic Offline Reinforcement Learning. - Di Wu; Yuling Jiao; Li Shen 008; Haizhao Yang; Xiliang Lu (AAAI, 2024)

Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits. - Zhan Yu; Qiuhao Chen; Yuling Jiao; Yinan Li; Xiliang Lu; Xin Wang; Jerry Zhijian Yang (NeurIPS, 2024)

Semi-Supervised Deep Sobolev Regression: Estimation, Variable Selection and Beyond. - Zhao Ding; Chenguang Duan; Yuling Jiao; Jerry Zhijian Yang (CoRR, 2024)

Deep Conditional Generative Learning: Model and Error Analysis. - Jinyuan Chang; Zhao Ding; Yuling Jiao; Ruoxuan Li; Jerry Zhijian Yang (CoRR, 2024)

A Stabilized Physics Informed Neural Networks Method for Wave Equations. - Yuling Jiao; Yuhui Liu; Jerry Zhijian Yang; Cheng Yuan (CoRR, 2024)

Convergence of Continuous Normalizing Flows for Learning Probability Distributions. - Yuan Gao; Jian Huang; Yuling Jiao; Shurong Zheng (CoRR, 2024)

Convergence Analysis of Flow Matching in Latent Space with Transformers. - Yuling Jiao; Yanming Lai; Yang Wang 020; Bokai Yan (CoRR, 2024)

Latent Schr{ "o}dinger Bridge Diffusion Model for Generative Learning. - Yuling Jiao; Lican Kang; Huazhen Lin; Jin Liu; Heng Zuo (CoRR, 2024)

Characteristic Learning for Provable One Step Generation. - Zhao Ding; Chenguang Duan; Yuling Jiao; Ruoxuan Li; Jerry Zhijian Yang; Pingwen Zhang (CoRR, 2024)

Error Analysis of Three-Layer Neural Network Trained with PGD for Deep Ritz Method. - Yuling Jiao; Yanming Lai; Yang Wang (CoRR, 2024)

Model Free Prediction with Uncertainty Assessment. - Yuling Jiao; Lican Kang; Jin Liu; Heng Peng; Heng Zuo (CoRR, 2024)

Quantum Compiling with Reinforcement Learning on a Superconducting Processor. - Z. T. Wang; Qiuhao Chen; Yuxuan Du; Z. H. Yang; Xiaoxia Cai; Kaixuan Huang; Jingning Zhang; Kai Xu; Jun Du; Yinan Li; Yuling Jiao; Xingyao Wu; et al. (CoRR, 2024)

DRM Revisited: A Complete Error Analysis. - Yuling Jiao; Ruoxuan Li; Peiying Wu; Jerry Zhijian Yang; Pingwen Zhang (CoRR, 2024)

Unsupervised Transfer Learning via Adversarial Contrastive Training. - Chenguang Duan; Yuling Jiao; Huazhen Lin; Wensen Ma; Jerry Zhijian Yang (CoRR, 2024)

Approximation Bounds for Recurrent Neural Networks with Application to Regression. - Yuling Jiao; Yang Wang; Bokai Yan (CoRR, 2024)

Deep Transfer Learning: Model Framework and Error Analysis. - Yuling Jiao; Huazhen Lin; Yuchen Luo; Jerry Zhijian Yang (CoRR, 2024)

Nonlinear Assimilation with Score-based Sequential Langevin Sampling. - Zhao Ding; Chenguang Duan; Yuling Jiao; Jerry Zhijian Yang; Cheng Yuan; Pingwen Zhang (CoRR, 2024)

A Gaussian mixture distribution-based adaptive sampling method for physics-informed neural networks. - Yuling Jiao; Di Li; Xiliang Lu; Jerry Zhijian Yang; Cheng Yuan (Eng. Appl. Artif. Intell., 2024)

An error analysis for deep binary classification with sigmoid loss. - Changshi Li; Yuling Jiao; Jerry Zhijian Yang (Inf. Sci., 2024)

Current density impedance imaging with PINNs. - Chenguang Duan; Junjun Huang; Yuling Jiao; Xiliang Lu; Jerry Zhijian Yang (J. Comput. Appl. Math., 2024)

Gaussian Interpolation Flows. - Yuan Gao 044; Jian Huang 003; Yuling Jiao (J. Mach. Learn. Res., 2024)

Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Joel L. Horowitz; Jian Huang 003 (J. Mach. Learn. Res., 2024)

Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models. - Changyu Liu; Yuling Jiao; Junhui Wang; Jian Huang 003 (SIAM J. Math. Data Sci., 2024)

Deep Ritz Method for Elliptical Multiple Eigenvalue Problems. - Xia Ji 001; Yuling Jiao; Xiliang Lu; Pengcheng Song; Fengru Wang (J. Sci. Comput., 2024)

Deep Dimension Reduction for Supervised Representation Learning. - Jian Huang 003; Yuling Jiao; Xu Liao; Jin Liu 011; Zhou Yu (IEEE Trans. Inf. Theory, 2024)

Relative Entropy Gradient Sampler for Unnormalized Distribution. - Xingdong Feng; Yuan Gao 044; Jian Huang 003; Yuling Jiao; Xu Liu 024 (J. Comput. Graph. Stat., 2025)

Convergence analysis of deep Ritz method with over-parameterization. - Zhao Ding; Yuling Jiao; Xiliang Lu; Peiying Wu; Jerry Zhijian Yang (Neural Networks, 2025)

Deep contrastive representation learning for supervised tasks. - Chenguang Duan; Yuling Jiao; Lican Kang; Jerry Zhijian Yang; Fusheng Zhou (Pattern Recognit., 2025)

Distribution Matching for Self-Supervised Transfer Learning. - Yuling Jiao; Wensen Ma; Defeng Sun; Hansheng Wang; Yang Wang (CoRR, 2025)

Schrödinger-Föllmer Sampler. - Jian Huang 003; Yuling Jiao; Lican Kang; Xu Liao; Jin Liu 011; Yanyan Liu (IEEE Trans. Inf. Theory, 2025)

Approximation Bounds for Transformer Networks with Application to Regression. - Yuling Jiao; Yanming Lai; Defeng Sun; Yang Wang; Bokai Yan (CoRR, 2025)

Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective. - Yuling Jiao; Yanming Lai; Yang Wang; Bokai Yan (CoRR, 2025)

Semi-Supervised Deep Sobolev Regression: Estimation and Variable Selection by ReQU Neural Network. - Zhao Ding; Chenguang Duan; Yuling Jiao; Jerry Zhijian Yang (IEEE Trans. Inf. Theory, 2025)

Boosting Statistic Learning with Synthetic Data from Pretrained Large Models. - Jialong Jiang; Wenkang Hu; Jian Huang; Yuling Jiao; Xu Liu (CoRR, 2025)

Wasserstein Distributionally Robust Nonparametric Regression. - Changyu Liu; Yuling Jiao; Junhui Wang; Jian Huang (CoRR, 2025)

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation. - Ningxin Gui; Qianghuai Jia; Feijun Jiang; Yuling Jiao; Dechun Wang; Jerry Zhijian Yang (CoRR, 2025)

Error Analysis of Three-Layer Neural Network Trained With PGD for Deep Ritz Method. - Yuling Jiao; Yanming Lai; Yang Wang 020 (IEEE Trans. Inf. Theory, 2025)

Model Free Prediction With Uncertainty Assessment. - Yuling Jiao; Lican Kang; Jin Liu 011; Heng Peng; Heng Zuo (IEEE Trans. Inf. Theory, 2025)