A New Coarse-to-Fine Framework for 3D Brain MR Image Registration. - Terrence Chen; Thomas S. Huang; Wotao Yin; Xiang Sean Zhou (CVBIA, 2005)

Illumination Normalization for Face Recognition and Uneven Background Correction Using Total Variation Based Image Models. - Terrence Chen; Wotao Yin; Xiang Sean Zhou; Dorin Comaniciu; Thomas S. Huang (CVPR (2), 2005)

Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L1 Functional. - Wotao Yin; Donald Goldfarb; Stanley J. Osher (VLSM, 2005)

Background correction for cDNA microarray images using the TV+L1 model. - Wotao Yin; Terrence Chen; Xiang Sean Zhou; Amit Chakraborty (Bioinform., 2005)

An Iterative Regularization Method for Total Variation-Based Image Restoration. - Stanley J. Osher; Martin Burger 001; Donald Goldfarb; Jinjun Xu; Wotao Yin (Multiscale Model. Simul., 2005)

Second-order Cone Programming Methods for Total Variation-Based Image Restoration. - Donald Goldfarb; Wotao Yin (SIAM J. Sci. Comput., 2005)

Total Variation Models for Variable Lighting Face Recognition. - Terrence Chen; Wotao Yin; Xiang Sean Zhou; Dorin Comaniciu; Thomas S. Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

A comparison of three total variation based texture extraction models. - Wotao Yin; Donald Goldfarb; Stanley J. Osher (J. Vis. Commun. Image Represent., 2007)

The Total Variation Regularized L1 Model for Multiscale Decomposition. - Wotao Yin; Donald Goldfarb; Stanley J. Osher (Multiscale Model. Simul., 2007)

An efficient algorithm for compressed MR imaging using total variation and wavelets. - Shiqian Ma; Wotao Yin; Yin Zhang 010; Amit Chakraborty (CVPR, 2008)

Iteratively reweighted algorithms for compressive sensing. - Rick Chartrand; Wotao Yin (ICASSP, 2008)

A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents - Simon P. Morgan; Wotao Yin; Kevin R. Vixie (CoRR, 2008)

A New Alternating Minimization Algorithm for Total Variation Image Reconstruction. - Yilun Wang; Junfeng Yang; Wotao Yin; Yin Zhang 010 (SIAM J. Imaging Sci., 2008)

Bregman Iterative Algorithms for ell1-Minimization with Applications to Compressed Sensing. - Wotao Yin; Stanley J. Osher; Donald Goldfarb; Jérôme Darbon (SIAM J. Imaging Sci., 2008)

Fixed-Point Continuation for l1-Minimization: Methodology and Convergence. - Elaine T. Hale; Wotao Yin; Yin Zhang 010 (SIAM J. Optim., 2008)

Compressed Sensing via Iterative Support Detection - Yilun Wang; Wotao Yin (CoRR, 2009)

A Curvilinear Search Method for p-Harmonic Flows on Spheres. - Donald Goldfarb; Zaiwen Wen; Wotao Yin (SIAM J. Imaging Sci., 2009)

A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration. - Junfeng Yang; Wotao Yin; Yin Zhang 010; Yilun Wang (SIAM J. Imaging Sci., 2009)

Parametric Maximum Flow Algorithms for Fast Total Variation Minimization. - Donald Goldfarb; Wotao Yin (SIAM J. Sci. Comput., 2009)

An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise. - Junfeng Yang; Yin Zhang 010; Wotao Yin (SIAM J. Sci. Comput., 2009)

Collaborative spectrum sensing from sparse observations using matrix completion for cognitive radio networks. - Jia (Jasmine) Meng; Wotao Yin; Husheng Li; Ekram Hossain 001; Zhu Han 001 (ICASSP, 2010)

EdgeCS: edge guided compressive sensing reconstruction. - Weihong Guo 002; Wotao Yin (VCIP, 2010)

Practical compressive sensing with Toeplitz and circulant matrices. - Wotao Yin; Simon P. Morgan; Junfeng Yang; Yin Zhang 010 (VCIP, 2010)

A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression. - Jianing Shi; Wotao Yin; Stanley J. Osher; Paul Sajda (J. Mach. Learn. Res., 2010)

A Fast Alternating Direction Method for TVL1-L2 Signal Reconstruction From Partial Fourier Data. - Junfeng Yang; Yin Zhang 010; Wotao Yin (IEEE J. Sel. Top. Signal Process., 2010)

Alternating direction augmented Lagrangian methods for semidefinite programming. - Zaiwen Wen; Donald Goldfarb; Wotao Yin (Math. Program. Comput., 2010)

Sparse Signal Reconstruction via Iterative Support Detection. - Yilun Wang; Wotao Yin (SIAM J. Imaging Sci., 2010)

Analysis and Generalizations of the Linearized Bregman Method. - Wotao Yin (SIAM J. Imaging Sci., 2010)

A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation. - Zaiwen Wen; Wotao Yin; Donald Goldfarb; Yin Zhang 010 (SIAM J. Sci. Comput., 2010)

Image-based face illumination transferring using logarithmic total variation models. - Qing Li 008; Wotao Yin; Zhigang Deng 001 (Vis. Comput., 2010)

Dynamic compressive spectrum sensing for cognitive radio networks. - Wotao Yin; Zaiwen Wen; Shuyi Li; Jia (Jasmine) Meng; Zhu Han 001 (CISS, 2011)

Oil spill sensor using multispectral infrared imaging via ℓ1 minimization. - Yingying Li; Wei-Chuan Shih; Zhu Han 001; Wotao Yin (ICASSP, 2011)

High Resolution OFDM Channel Estimation with Low Speed ADC Using Compressive Sensing. - Jia (Jasmine) Meng; Yingying Li; Nam Tuan Nguyen; Wotao Yin; Zhu Han 001 (ICC, 2011)

An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors - Yangyang Xu; Wotao Yin; Zaiwen Wen; Yin Zhang 010 (CoRR, 2011)

Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising - Stanley J. Osher; Yu Mao; Bin Dong 001; Wotao Yin (CoRR, 2011)

Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks. - Jia (Jasmine) Meng; Wotao Yin; Husheng Li; Ekram Hossain 001; Zhu Han 001 (IEEE J. Sel. Areas Commun., 2011)

Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements. - Jason N. Laska; Zaiwen Wen; Wotao Yin; Richard G. Baraniuk (IEEE Trans. Signal Process., 2011)

Signal representations with minimum ℓ∞-norm. - Christoph Studer; Wotao Yin; Richard G. Baraniuk (Allerton Conference, 2012)

Decentralized low-rank matrix completion. - Qing Ling 001; Yangyang Xu; Wotao Yin; Zaiwen Wen (ICASSP, 2012)

Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models. - Po-Sen Huang; Mark Hasegawa-Johnson; Wotao Yin; Thomas S. Huang (MLSP, 2012)

Augmented L1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm - Ming-Jun Lai; Wotao Yin (CoRR, 2012)

Necessary and sufficient conditions of solution uniqueness in ℓ1 minimization - Hui Zhang 050; Wotao Yin; Lizhi Cheng (CoRR, 2012)

Copula density estimation by total variation penalized likelihood with linear equality constraints. - Leming Qu; Wotao Yin (Comput. Stat. Data Anal., 2012)

A multi-block alternating direction method with parallel splitting for decentralized consensus optimization. - Qing Ling 001; Min Tao; Wotao Yin; Xiaoming Yuan 001 (EURASIP J. Wirel. Commun. Netw., 2012)

Compressive Sensing Based High-Resolution Channel Estimation for OFDM System. - Jia (Jasmine) Meng; Wotao Yin; Yingying Li; Nam Tuan Nguyen; Zhu Han 001 (IEEE J. Sel. Top. Signal Process., 2012)

Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm. - Zaiwen Wen; Wotao Yin; Yin Zhang 010 (Math. Program. Comput., 2012)

On the convergence of an active-set method for ℓ1 minimization. - Zaiwen Wen; Wotao Yin; Hongchao Zhang; Donald Goldfarb (Optim. Methods Softw., 2012)

Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging. - Yunmei Chen; William W. Hager; Feng Huang 001; Dzung T. Phan; Xiaojing Ye; Wotao Yin (SIAM J. Imaging Sci., 2012)

Edge Guided Reconstruction for Compressive Imaging. - Weihong Guo 002; Wotao Yin (SIAM J. Imaging Sci., 2012)

Parallel and distributed sparse optimization. - Zhimin Peng; Ming Yan 006; Wotao Yin (ACSSC, 2013)

Mixing space-time derivatives for video compressive sensing. - Yi Yang 010; Hayden Schaeffer; Wotao Yin; Stanley J. Osher (ACSSC, 2013)

A linearized bregman algorithm for decentralized basis pursuit. - Kun Yuan 001; Qing Ling 001; Wotao Yin; Alejandro Ribeiro (EUSIPCO, 2013)

Linearly convergent decentralized consensus optimization with the alternating direction method of multipliers. - Wei Shi 010; Qing Ling 001; Kun Yuan 001; Gang Wu 011; Wotao Yin (ICASSP, 2013)

A distribute parallel approach for big data scale optimal power flow with security constraints. - Lanchao Liu; Amin Khodaei; Wotao Yin; Zhu Han 001 (SmartGridComm, 2013)

Optimal sparse kernel learning for hyperspectral anomaly detection. - Prudhvi Gurram; Heesung Kwon; Zhimin Peng; Wotao Yin (WHISPERS, 2013)

An efficient augmented Lagrangian method with applications to total variation minimization. - Chengbo Li; Wotao Yin; Hong Jiang 002; Yin Zhang 010 (Comput. Optim. Appl., 2013)

Parallel matrix factorization for low-rank tensor completion. - Yangyang Xu; Ruru Hao; Wotao Yin; Zhixun Su (CoRR, 2013)

A dual algorithm for a class of augmented convex models. - Hui Zhang 050; Lizhi Cheng; Wotao Yin (CoRR, 2013)

Gradient methods for convex minimization: better rates under weaker conditions - Hui Zhang 050; Wotao Yin (CoRR, 2013)

One condition for all: solution uniqueness and robustness of ℓ1-synthesis and ℓ1-analysis minimizations - Hui Zhang 050; Ming Yan 006; Wotao Yin (CoRR, 2013)

Error Forgetting of Bregman Iteration. - Wotao Yin; Stanley J. Osher (J. Sci. Comput., 2013)

A feasible method for optimization with orthogonality constraints. - Zaiwen Wen; Wotao Yin (Math. Program., 2013)

Augmented 퓁1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm. - Ming-Jun Lai; Wotao Yin (SIAM J. Imaging Sci., 2013)

A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion. - Yangyang Xu; Wotao Yin (SIAM J. Imaging Sci., 2013)

Improved Iteratively Reweighted Least Squares for Unconstrained Smoothed 퓁q Minimization. - Ming-Jun Lai; Yangyang Xu; Wotao Yin (SIAM J. Numer. Anal., 2013)

Decentralized Jointly Sparse Optimization by Reweighted lq Minimization. - Qing Ling 001; Zaiwen Wen; Wotao Yin (IEEE Trans. Signal Process., 2013)

Video Compressive Sensing for Dynamic MRI. - Jianing Shi; Wotao Yin; Aswin C. Sankaranarayanan; Richard G. Baraniuk (CoRR, 2014)

Democratic Representations. - Christoph Studer; Tom Goldstein; Wotao Yin; Richard G. Baraniuk (CoRR, 2014)

A fast patch-dictionary method for whole image recovery. - Yangyang Xu; Wotao Yin (CoRR, 2014)

Folding-Free Global Conformal Mapping for Genus-0 Surfaces by Harmonic Energy Minimization. - Rongjie Lai; Zaiwen Wen; Wotao Yin; Xianfeng Gu; Lok Ming Lui (J. Sci. Comput., 2014)

A New Detail-Preserving Regularization Scheme. - Weihong Guo 002; Jing Qin 003; Wotao Yin (SIAM J. Imaging Sci., 2014)

On the Linear Convergence of the ADMM in Decentralized Consensus Optimization. - Wei Shi 010; Qing Ling 001; Kun Yuan 001; Gang Wu 011; Wotao Yin (IEEE Trans. Signal Process., 2014)

Prediction of High Resolution Spatial-Temporal Air Pollutant Map from Big Data Sources. - Yingyu Li; Yifang Zhu; Wotao Yin; Yang Liu 037; Guangming Shi; Zhu Han 001 (BigCom, 2015)

A proximal gradient algorithm for decentralized nondifferentiable optimization. - Wei Shi 010; Qing Ling 001; Gang Wu 011; Wotao Yin (ICASSP, 2015)

ExtraPush for Convex Smooth Decentralized Optimization over Directed Networks. - Jinshan Zeng; Wotao Yin (CoRR, 2015)

Necessary and Sufficient Conditions of Solution Uniqueness in 1-Norm Minimization. - Hui Zhang 050; Wotao Yin; Lizhi Cheng (J. Optim. Theory Appl., 2015)

EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization. - Wei Shi 010; Qing Ling 001; Gang Wu 011; Wotao Yin (SIAM J. Optim., 2015)

Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization. - Yangyang Xu; Wotao Yin (SIAM J. Optim., 2015)

Sparse kernel learning-based feature selection for anomaly detection. - Zhimin Peng; Prudhvi Gurram; Heesung Kwon; Wotao Yin (IEEE Trans. Aerosp. Electron. Syst., 2015)

NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings. - Chinmay Hegde; Aswin C. Sankaranarayanan; Wotao Yin; Richard G. Baraniuk (IEEE Trans. Signal Process., 2015)

A Proximal Gradient Algorithm for Decentralized Composite Optimization. - Wei Shi 010; Qing Ling 001; Gang Wu 011; Wotao Yin (IEEE Trans. Signal Process., 2015)

Expander graph and communication-efficient decentralized optimization. - Yat Tin Chow; Wei Shi 010; Tianyu Wu; Wotao Yin (ACSSC, 2016)

One condition for solution uniqueness and robustness of both l1-synthesis and l1-analysis minimizations. - Hui Zhang 050; Ming Yan 006; Wotao Yin (Adv. Comput. Math., 2016)

Coordinate Friendly Structures, Algorithms and Applications. - Zhimin Peng; Tianyu Wu; Yangyang Xu; Ming Yan 006; Wotao Yin (CoRR, 2016)

On the Convergence of Asynchronous Parallel Iteration with Arbitrary Delays. - Zhimin Peng; Yangyang Xu; Ming Yan 006; Wotao Yin (CoRR, 2016)

On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers. - Wei Deng; Wotao Yin (J. Sci. Comput., 2016)

On the Convergence of Decentralized Gradient Descent. - Kun Yuan 001; Qing Ling 001; Wotao Yin (SIAM J. Optim., 2016)

ARock: An Algorithmic Framework for Asynchronous Parallel Coordinate Updates. - Zhimin Peng; Yangyang Xu; Ming Yan 006; Wotao Yin (SIAM J. Sci. Comput., 2016)

Decentralized bundle method for nonsmooth consensus optimization. - Zifeng Wang 003; Qing Ling 001; Wotao Yin (GlobalSIP, 2017)

Online convolutional dictionary learning. - Jialin Liu 003; Cristina Garcia-Cardona; Brendt Wohlberg; Wotao Yin (ICIP, 2017)

Robust linear unmixing with enhanced sparsity. - Alexandre Tiard; Laurent Condat; Lucas Drumetz; Jocelyn Chanussot; Wotao Yin; Xiaoxiang Zhu 001 (ICIP, 2017)

Accelerated high-resolution EEG source imaging. - Jing Qin 003; Tianyu Wu; Ying Li 009; Wotao Yin; Stanley J. Osher; Wentai Liu (NER, 2017)

Straggler Mitigation in Distributed Optimization Through Data Encoding. - Can Karakus; Yifan Sun 001; Suhas N. Diggavi; Wotao Yin (NIPS, 2017)

Asynchronous Coordinate Descent under More Realistic Assumptions. - Tao Sun 005; Robert Hannah; Wotao Yin (NIPS, 2017)

A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs. - Yanli Liu 003; Ernest K. Ryu; Wotao Yin (CoRR, 2017)

More Iterations per Second, Same Quality - Why Asynchronous Algorithms may Drastically Outperform Traditional Ones. - Robert Hannah; Wotao Yin (CoRR, 2017)

Algorithm for Overcoming the Curse of Dimensionality For Time-Dependent Non-convex Hamilton-Jacobi Equations Arising From Optimal Control and Differential Games Problems. - Yat Tin Chow; Jérôme Darbon; Stanley J. Osher; Wotao Yin (J. Sci. Comput., 2017)

Parallel Multi-Block ADMM with o(1 / k) Convergence. - Wei Deng; Ming-Jun Lai; Zhimin Peng; Wotao Yin (J. Sci. Comput., 2017)

A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update. - Yangyang Xu; Wotao Yin (J. Sci. Comput., 2017)

Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions. - Damek Davis; Wotao Yin (Math. Oper. Res., 2017)

Cyclic Coordinate-Update Algorithms for Fixed-Point Problems: Analysis and Applications. - Yat Tin Chow; Tianyu Wu; Wotao Yin (SIAM J. Sci. Comput., 2017)

Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds. - Xiaohan Chen; Jialin Liu 003; Zhangyang Wang; Wotao Yin (NeurIPS, 2018)

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning. - Tianyi Chen; Georgios B. Giannakis; Tao Sun 005; Wotao Yin (NeurIPS, 2018)

Breaking the Span Assumption Yields Fast Finite-Sum Minimization. - Robert Hannah; Yanli Liu 003; Daniel O'Connor; Wotao Yin (NeurIPS, 2018)

On Markov Chain Gradient Descent. - Tao Sun 005; Yuejiao Sun; Wotao Yin (NeurIPS, 2018)

A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. - Wotao Yin; Xianghui Mao; Kun Yuan 001; Yuantao Gu; Ali H. Sayed (CoRR, 2018)

AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Reinforcement Learning with Near-Optimal Sample Complexity. - Yibo Zeng; Fei Feng; Wotao Yin (CoRR, 2018)

Parallel redistancing using the Hopf-Lax formula. - Michael Royston; Andre Pradhana; Byungjoon Lee 001; Yat Tin Chow; Wotao Yin; Joseph Teran; Stanley J. Osher (J. Comput. Phys., 2018)

On Unbounded Delays in Asynchronous Parallel Fixed-Point Algorithms. - Robert Hannah; Wotao Yin (J. Sci. Comput., 2018)

A Parallel Method for Earth Mover's Distance. - Wuchen Li; Ernest K. Ryu; Stanley J. Osher; Wotao Yin; Wilfrid Gangbo (J. Sci. Comput., 2018)

Cauchy Noise Removal by Nonconvex ADMM with Convergence Guarantees. - Jin-Jin Mei; Yiqiu Dong; Ting-Zhu Huang; Wotao Yin (J. Sci. Comput., 2018)

First- and Second-Order Methods for Online Convolutional Dictionary Learning. - Jialin Liu 003; Cristina Garcia-Cardona; Brendt Wohlberg; Wotao Yin (SIAM J. Imaging Sci., 2018)

A Fast and Accurate Basis Pursuit Denoising Algorithm With Application to Super-Resolving Tomographic SAR. - Yilei Shi; Xiao Xiang Zhu 001; Wotao Yin; Richard Bamler (IEEE Trans. Geosci. Remote. Sens., 2018)

Learning Collaborative Sparsity Structure via Nonconvex Optimization for Feature Recognition. - Zhaohui Du; Xuefeng Chen 002; Han Zhang 036; Ruqiang Yan 001; Wotao Yin (IEEE Trans. Ind. Informatics, 2018)

Decentralized Consensus Optimization With Asynchrony and Delays. - Tianyu Wu; Kun Yuan 001; Qing Ling 001; Wotao Yin; Ali H. Sayed (IEEE Trans. Signal Inf. Process. over Networks, 2018)

On Nonconvex Decentralized Gradient Descent. - Jinshan Zeng; Wotao Yin (IEEE Trans. Signal Process., 2018)

A Distributed ADMM Approach With Decomposition-Coordination for Mobile Data Offloading. - Yingyu Li; Guangming Shi; Wotao Yin; Lanchao Liu; Zhu Han 001 (IEEE Trans. Veh. Technol., 2018)

On the Comparison between Primal and Primal-dual Methods in Decentralized Dynamic Optimization. - Wei Xu 010; Kun Yuan 001; Wotao Yin; Qing Ling 001 (ACSSC, 2019)

A2BCD: Asynchronous Acceleration with Optimal Complexity. - Robert Hannah; Fei Feng; Wotao Yin (ICLR (Poster), 2019)

ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. - Jialin Liu 003; Xiaohan Chen; Zhangyang Wang; Wotao Yin (ICLR (Poster), 2019)

Acceleration of SVRG and Katyusha X by Inexact Preconditioning. - Yanli Liu 003; Fei Feng; Wotao Yin (ICML, 2019)

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. - Ernest K. Ryu; Jialin Liu 003; Sicheng Wang 003; Xiaohan Chen; Zhangyang Wang; Wotao Yin (ICML, 2019)

Douglas-Rachford splitting and ADMM for pathological convex optimization. - Ernest K. Ryu; Yanli Liu 003; Wotao Yin (Comput. Optim. Appl., 2019)

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs. - Ernest K. Ryu; Kun Yuan 001; Wotao Yin (CoRR, 2019)

XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training. - Lei Guan; Wotao Yin; Dongsheng Li 001; Xicheng Lu (CoRR, 2019)

Does Knowledge Transfer Always Help to Learn a Better Policy? - Fei Feng; Wotao Yin; Lin F. Yang (CoRR, 2019)

Walk Proximal Gradient: An Energy-Efficient Algorithm for Consensus Optimization. - Xianghui Mao; Yuantao Gu; Wotao Yin (IEEE Internet Things J., 2019)

Algorithm for overcoming the curse of dimensionality for state-dependent Hamilton-Jacobi equations. - Yat Tin Chow; Jérôme Darbon; Stanley J. Osher; Wotao Yin (J. Comput. Phys., 2019)

Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. - Can Karakus; Yifan Sun 001; Suhas N. Diggavi; Wotao Yin (J. Mach. Learn. Res., 2019)

An Envelope for Davis-Yin Splitting and Strict Saddle-Point Avoidance. - Yanli Liu 003; Wotao Yin (J. Optim. Theory Appl., 2019)

Algorithm for Hamilton-Jacobi Equations in Density Space Via a Generalized Hopf Formula. - Yat Tin Chow; Wuchen Li; Stanley J. Osher; Wotao Yin (J. Sci. Comput., 2019)

Global Convergence of ADMM in Nonconvex Nonsmooth Optimization. - Yu Wang 075; Wotao Yin; Jinshan Zeng (J. Sci. Comput., 2019)

Run-and-Inspect Method for nonconvex optimization and global optimality bounds for R-local minimizers. - Yifan Chen; Yuejiao Sun; Wotao Yin (Math. Program., 2019)

A new use of Douglas-Rachford splitting for identifying infeasible, unbounded, and pathological conic programs. - Yanli Liu 003; Ernest K. Ryu; Wotao Yin (Math. Program., 2019)

Denoising Prior Driven Deep Neural Network for Image Restoration. - Weisheng Dong; Peiyao Wang; Wotao Yin; Guangming Shi; Fangfang Wu; Xiaotong Lu (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Consistent Dynamic Mode Decomposition. - Omri Azencot; Wotao Yin; Andrea L. Bertozzi (SIAM J. Appl. Dyn. Syst., 2019)

AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity. - Yibo Zeng; Fei Feng; Wotao Yin (AISTATS, 2020)

An Improved Analysis of Stochastic Gradient Descent with Momentum. - Yanli Liu 003; Yuan Gao; Wotao Yin (NeurIPS, 2020)

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning. - Fei Feng; Ruosong Wang; Wotao Yin; Simon S. Du; Lin F. Yang (NeurIPS, 2020)

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. - Yanli Liu 003; Kaiqing Zhang; Tamer Basar; Wotao Yin (NeurIPS, 2020)

Markov chain block coordinate descent. - Tao Sun 005; Yuejiao Sun; Yangyang Xu; Wotao Yin (Comput. Optim. Appl., 2020)

Scaled Relative Graph of Normal Matrices. - Xinmeng Huang; Ernest K. Ryu; Wotao Yin (CoRR, 2020)

LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning. - Tianyi Chen; Yuejiao Sun; Wotao Yin (CoRR, 2020)

Provably Efficient Exploration for RL with Unsupervised Learning. - Fei Feng; Ruosong Wang; Wotao Yin; Simon S. Du; Lin F. Yang (CoRR, 2020)

FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data. - Xinwei Zhang 001; Mingyi Hong 001; Sairaj V. Dhople; Wotao Yin; Yang Liu 165 (CoRR, 2020)

VAFL: a Method of Vertical Asynchronous Federated Learning. - Tianyi Chen; Xiao Jin; Yuejiao Sun; Wotao Yin (CoRR, 2020)

Projecting to Manifolds via Unsupervised Learning. - Howard Heaton; Samy Wu Fung; Alex Tong Lin; Stanley J. Osher; Wotao Yin (CoRR, 2020)

SCOBO: Sparsity-Aware Comparison Oracle Based Optimization. - HanQin Cai; Daniel McKenzie; Wotao Yin; Zhenliang Zhang 001 (CoRR, 2020)

Attentional Biased Stochastic Gradient for Imbalanced Classification. - Qi Qi 006; Yi Xu 008; Rong Jin 001; Wotao Yin; Tianbao Yang (CoRR, 2020)

Hybrid Federated Learning: Algorithms and Implementation. - Xinwei Zhang 001; Wotao Yin; Mingyi Hong 001; Tianyi Chen (CoRR, 2020)

Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers. - Chun-Na Li 001; Yuan-Hai Shao 001; Wotao Yin; Ming-Zeng Liu (IEEE Trans. Neural Networks Learn. Syst., 2020)

Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. - Huan Li 007; Cong Fang 001; Wotao Yin; Zhouchen Lin (IEEE Trans. Signal Process., 2020)

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. - Xianghui Mao; Kun Yuan 001; Yubin Hu 001; Yuantao Gu; Ali H. Sayed; Wotao Yin (IEEE Trans. Signal Process., 2020)

CADA: Communication-Adaptive Distributed Adam. - Tianyi Chen; Ziye Guo; Yuejiao Sun; Wotao Yin (AISTATS, 2021)

An Optimal Stochastic Compositional Optimization Method with Applications to Meta Learning. - Yuejiao Sun; Tianyi Chen; Wotao Yin (ICASSP, 2021)

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. - Kun Yuan 001; Yiming Chen 003; Xinmeng Huang; Yingya Zhang; Pan Pan; Yinghui Xu; Wotao Yin (ICCV, 2021)

Learning A Minimax Optimizer: A Pilot Study. - Jiayi Shen; Xiaohan Chen; Howard Heaton; Tianlong Chen 001; Jialin Liu 003; Wotao Yin; Zhangyang Wang (ICLR, 2021)

A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization. - HanQin Cai; Yuchen Lou; Daniel McKenzie; Wotao Yin (ICML, 2021)

Accelerating Gossip SGD with Periodic Global Averaging. - Yiming Chen 003; Kun Yuan 001; Yingya Zhang; Pan Pan; Yinghui Xu; Wotao Yin (ICML, 2021)

Provably Correct Optimization and Exploration with Non-linear Policies. - Fei Feng; Wotao Yin; Alekh Agarwal; Lin Yang 011 (ICML, 2021)

AutoBandit: A Meta Bandit Online Learning System. - Miao Xie; Wotao Yin; Huan Xu (IJCAI, 2021)

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. - HanQin Cai; Jialin Liu 003; Wotao Yin (NeurIPS, 2021)

Hyperparameter Tuning is All You Need for LISTA. - Xiaohan Chen; Jialin Liu 003; Zhangyang Wang; Wotao Yin (NeurIPS, 2021)

Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems. - Tianyi Chen; Yuejiao Sun; Wotao Yin (NeurIPS, 2021)

An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders. - Xinmeng Huang; Kun Yuan 001; Xianghui Mao; Wotao Yin (NeurIPS, 2021)

Exponential Graph is Provably Efficient for Decentralized Deep Training. - Bicheng Ying; Kun Yuan 001; Yiming Chen 003; Hanbin Hu; Pan Pan; Wotao Yin (NeurIPS, 2021)

A Single-Timescale Stochastic Bilevel Optimization Method. - Tianyi Chen; Yuejiao Sun; Wotao Yin (CoRR, 2021)

Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop. - Samy Wu Fung; Howard Heaton; Qiuwei Li; Daniel McKenzie; Stanley J. Osher; Wotao Yin (CoRR, 2021)

On the Comparison between Cyclic Sampling and Random Reshuffling. - Xinmeng Huang; Kun Yuan 001; Xianghui Mao; Wotao Yin (CoRR, 2021)

Feasibility-based Fixed Point Networks. - Howard Heaton; Samy Wu Fung; Aviv Gibali; Wotao Yin (CoRR, 2021)

On Stochastic Moving-Average Estimators for Non-Convex Optimization. - Zhishuai Guo; Yi Xu 008; Wotao Yin; Rong Jin 001; Tianbao Yang (CoRR, 2021)

Learn to Predict Equilibria via Fixed Point Networks. - Howard Heaton; Daniel McKenzie; Qiuwei Li; Samy Wu Fung; Stanley J. Osher; Wotao Yin (CoRR, 2021)

Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems. - Tianyi Chen; Yuejiao Sun; Wotao Yin (CoRR, 2021)

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning. - Bicheng Ying; Kun Yuan 001; Hanbin Hu; Yiming Chen 003; Wotao Yin (CoRR, 2021)

A Novel Convergence Analysis for Algorithms of the Adam Family. - Zhishuai Guo; Yi Xu 008; Wotao Yin; Rong Jin 001; Tianbao Yang (CoRR, 2021)

Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures. - Yanli Liu 003; Yunbei Xu; Wotao Yin (J. Sci. Comput., 2021)

Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances. - Jialin Liu 003; Wotao Yin; Wuchen Li; Yat Tin Chow (SIAM J. Sci. Comput., 2021)

Communication-Adaptive Stochastic Gradient Methods for Distributed Learning. - Tianyi Chen; Yuejiao Sun; Wotao Yin (IEEE Trans. Signal Process., 2021)

Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization. - Tianyi Chen; Yuejiao Sun; Wotao Yin (IEEE Trans. Signal Process., 2021)

Decentralized Learning With Lazy and Approximate Dual Gradients. - Yanli Liu 003; Yuejiao Sun; Wotao Yin (IEEE Trans. Signal Process., 2021)

FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data. - Xinwei Zhang 001; Mingyi Hong 001; Sairaj V. Dhople; Wotao Yin; Yang Liu 165 (IEEE Trans. Signal Process., 2021)

JFB: Jacobian-Free Backpropagation for Implicit Networks. - Samy Wu Fung; Howard Heaton; Qiuwei Li; Daniel McKenzie; Stanley J. Osher; Wotao Yin (AAAI, 2022)

A Single-Timescale Method for Stochastic Bilevel Optimization. - Tianyi Chen; Yuejiao Sun; Quan Xiao; Wotao Yin (AISTATS, 2022)

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. - Xinmeng Huang; Yiming Chen 003; Wotao Yin; Kun Yuan 001 (NeurIPS, 2022)

Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. - Zhuoqing Song; Weijian Li; Kexin Jin; Lei Shi 010; Ming Yan 006; Wotao Yin; Kun Yuan 001 (NeurIPS, 2022)

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. - Tian Zhou 004; Ziqing Ma; Xue Wang 010; Qingsong Wen; Liang Sun 001; Tao Yao; Wotao Yin; Rong Jin 001 (NeurIPS, 2022)

On Representing Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Jianfeng Lu 001; Wotao Yin (CoRR, 2022)

On Representing Mixed-Integer Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Jianfeng Lu 001; Wotao Yin (CoRR, 2022)

Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization. - Quan Xiao; Han Shen; Wotao Yin; Tianyi Chen (CoRR, 2022)

Learning to Optimize: A Primer and A Benchmark. - Tianlong Chen 001; Xiaohan Chen; Wuyang Chen 001; Howard Heaton; Jialin Liu 003; Zhangyang Wang; Wotao Yin (J. Mach. Learn. Res., 2022)

A Mean Field Game Inverse Problem. - Lisang Ding; Wuchen Li; Stanley J. Osher; Wotao Yin (J. Sci. Comput., 2022)

A Multiscale Semi-Smooth Newton Method for Optimal Transport. - Yiyang Liu; Zaiwen Wen; Wotao Yin (J. Sci. Comput., 2022)

Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints. - Jinshan Zeng; Wotao Yin; Ding-Xuan Zhou (J. Sci. Comput., 2022)

Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry. - Ernest K. Ryu; Robert Hannah; Wotao Yin (Math. Program., 2022)

On the geometric analysis of a quartic-quadratic optimization problem under a spherical constraint. - Haixiang Zhang; Andre Milzarek; Zaiwen Wen; Wotao Yin (Math. Program., 2022)

Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling. - HanQin Cai; Daniel McKenzie; Wotao Yin; Zhenliang Zhang 001 (SIAM J. Optim., 2022)

Wasserstein-Based Projections with Applications to Inverse Problems. - Howard Heaton; Samy Wu Fung; Alex Tong Lin; Stanley J. Osher; Wotao Yin (SIAM J. Math. Data Sci., 2022)

Safeguarded Learned Convex Optimization. - Howard Heaton; Xiaohan Chen; Zhangyang Wang; Wotao Yin (AAAI, 2023)

HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent. - Ziang Chen; Jianfeng Lu 001; Huajie Qian; Xinshang Wang; Wotao Yin (AISTATS, 2023)

Alternating Projected SGD for Equality-constrained Bilevel Optimization. - Quan Xiao; Han Shen; Wotao Yin; Tianyi Chen (AISTATS, 2023)

On Representing Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (ICLR, 2023)

On Representing Mixed-Integer Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (ICLR, 2023)

Towards Constituting Mathematical Structures for Learning to Optimize. - Jialin Liu 003; Xiaohan Chen; Zhangyang Wang; Wotao Yin; HanQin Cai (ICML, 2023)

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. - Lisang Ding; Kexin Jin; Bicheng Ying; Kun Yuan 001; Wotao Yin (ICML, 2023)

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression. - Yutong He; Xinmeng Huang; Yiming Chen 003; Wotao Yin; Kun Yuan 001 (CoRR, 2023)

MindOpt Tuner: Boost the Performance of Numerical Software by Automatic Parameter Tuning. - Mengyuan Zhang 003; Wotao Yin; Mengchang Wang; Yangbin Shen; Peng Xiang; You Wu; Liang Zhao; Junqiu Pan; Hu Jiang; KuoLing Huang (CoRR, 2023)

A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability. - Ming Jin 002; Bilgehan Sel; Fnu Hardeep; Wotao Yin (CoRR, 2023)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Wang 004; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (CoRR, 2023)

MindOpt Adapter for CPLEX Benchmarking Performance Analysis. - Mou Sun; Tao Li; Wotao Yin (CoRR, 2023)

Attentional-Biased Stochastic Gradient Descent. - Qi Qi 006; Yi Xu 008; Wotao Yin; Rong Jin 001; Tianbao Yang (Trans. Mach. Learn. Res., 2023)

BC-Prover: Backward Chaining Prover for Formal Theorem Proving. - Yuhang He; Jihai Zhang 001; Jianzhu Bao; Fangquan Lin; Cheng Yang 008; Bing Qin 001; Ruifeng Xu 001; Wotao Yin (EMNLP, 2024)

Efficient Algorithms for Sum-Of-Minimum Optimization. - Lisang Ding; Ziang Chen; Xinshang Wang; Wotao Yin (ICML, 2024)

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares. - Liangzu Peng; Wotao Yin (ICML, 2024)

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. - Yihua Zhang; Pingzhi Li; Junyuan Hong; Jiaxiang Li; Yimeng Zhang; Wenqing Zheng; Pin-Yu Chen; Jason D. Lee; Wotao Yin; Mingyi Hong 001; Zhangyang Wang; Sijia Liu 001; et al. (ICML, 2024)

Solving General Natural-Language-Description Optimization Problems with Large Language Models. - Jihai Zhang 001; Wei Wang; Siyan Guo; Li Wang 134; Fangquan Lin; Cheng Yang 008; Wotao Yin (NAACL (Industry Track), 2024)

Rethinking the Capacity of Graph Neural Networks for Branching Strategy. - Ziang Chen; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Wotao Yin (NeurIPS, 2024)

Democratizing Energy Management with LLM-Assisted Optimization Autoformalism. - Ming Jin 002; Bilgehan Sel; Fnu Hardeep; Wotao Yin (SmartGridComm, 2024)

Bagging Improves Generalization Exponentially. - Huajie Qian; Donghao Ying; Henry Lam; Wotao Yin (CoRR, 2024)

Learning to optimize: A tutorial for continuous and mixed-integer optimization. - Xiaohan Chen; Jialin Liu 003; Wotao Yin (CoRR, 2024)

ODE-based Learning to Optimize. - Zhonglin Xie; Wotao Yin; Zaiwen Wen (CoRR, 2024)

Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. - Ziang Chen; Xiaohan Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (CoRR, 2024)

S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (CoRR, 2024)

Decomposition Methods for Global Solution of Mixed-Integer Linear Programs. - Kaizhao Sun; Mou Sun; Wotao Yin (SIAM J. Optim., 2024)

Three-Operator Splitting for Learning to Predict Equilibria in Convex Games. - Daniel McKenzie; Howard Heaton; Qiuwei Li; Samy Wu Fung; Stanley J. Osher; Wotao Yin (SIAM J. Math. Data Sci., 2024)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Peter Wang; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (Trans. Mach. Learn. Res., 2024)

Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation. - Xinwei Zhang 001; Wotao Yin; Mingyi Hong 001; Tianyi Chen (Trans. Mach. Learn. Res., 2024)

S$^ text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (IEEE J. Sel. Top. Signal Process., 2024)

SymAgent: A Neural-Symbolic Self-Learning Agent Framework for Complex Reasoning over Knowledge Graphs. - Ben Liu; Jihai Zhang 001; Fangquan Lin; Cheng Yang 008; Min Peng 002; Wotao Yin (WWW, 2025)

Deeply Learned Robust Matrix Completion for Large-scale Low-rank Data Recovery. - HanQin Cai; Chandra Kundu; Jialin Liu 003; Wotao Yin (CoRR, 2025)

ComPO: Preference Alignment via Comparison Oracles. - Peter Chen; Xi Chen; Wotao Yin; Tianyi Lin (CoRR, 2025)

Curvature-Aware Derivative-Free Optimization. - Bumsu Kim; Daniel McKenzie; HanQin Cai; Wotao Yin (J. Sci. Comput., 2025)

AdapThink: Adaptive Thinking Preferences for Reasoning Language Model. - Xu Wan 001; Wei Wang; Wenyue Xu; Wotao Yin; Jie Song; Mingyang Sun (CoRR, 2025)