Wotao Yin

Orcid: 0000-0001-6697-9731

According to our database1, Wotao Yin authored at least 227 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

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Bibliography

2024
Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation.
Trans. Mach. Learn. Res., 2024

Decomposition Methods for Global Solution of Mixed-Integer Linear Programs.
SIAM J. Optim., 2024

S<sup>3</sup>Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching.
CoRR, 2024

Solving General Natural-Language-Description Optimization Problems with Large Language Models.
CoRR, 2024

Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs.
CoRR, 2024

ODE-based Learning to Optimize.
CoRR, 2024

Learning to optimize: A tutorial for continuous and mixed-integer optimization.
CoRR, 2024

Bagging Improves Generalization Exponentially.
CoRR, 2024

Rethinking the Capacity of Graph Neural Networks for Branching Strategy.
CoRR, 2024

Democratizing Energy Management with LLM-Assisted Optimization Autoformalism.
Proceedings of the IEEE International Conference on Communications, 2024

Solving General Natural-Language-Description Optimization Problems with Large Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 2024

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Algorithms for Sum-Of-Minimum Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

BC-Prover: Backward Chaining Prover for Formal Theorem Proving.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Attentional-Biased Stochastic Gradient Descent.
Trans. Mach. Learn. Res., 2023

MindOpt Adapter for CPLEX Benchmarking Performance Analysis.
CoRR, 2023

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee.
CoRR, 2023

A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability.
CoRR, 2023

MindOpt Tuner: Boost the Performance of Numerical Software by Automatic Parameter Tuning.
CoRR, 2023

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression.
CoRR, 2023

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm.
Proceedings of the International Conference on Machine Learning, 2023

Towards Constituting Mathematical Structures for Learning to Optimize.
Proceedings of the International Conference on Machine Learning, 2023

On Representing Mixed-Integer Linear Programs by Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

On Representing Linear Programs by Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Alternating Projected SGD for Equality-constrained Bilevel Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Safeguarded Learned Convex Optimization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Wasserstein-Based Projections with Applications to Inverse Problems.
SIAM J. Math. Data Sci., 2022

Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling.
SIAM J. Optim., 2022

On the geometric analysis of a quartic-quadratic optimization problem under a spherical constraint.
Math. Program., 2022

Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry.
Math. Program., 2022

Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints.
J. Sci. Comput., 2022

A Multiscale Semi-Smooth Newton Method for Optimal Transport.
J. Sci. Comput., 2022

A Mean Field Game Inverse Problem.
J. Sci. Comput., 2022

Learning to Optimize: A Primer and A Benchmark.
J. Mach. Learn. Res., 2022

Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization.
CoRR, 2022

On Representing Mixed-Integer Linear Programs by Graph Neural Networks.
CoRR, 2022

On Representing Linear Programs by Graph Neural Networks.
CoRR, 2022

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Single-Timescale Method for Stochastic Bilevel Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

JFB: Jacobian-Free Backpropagation for Implicit Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data.
IEEE Trans. Signal Process., 2021

Decentralized Learning With Lazy and Approximate Dual Gradients.
IEEE Trans. Signal Process., 2021

Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization.
IEEE Trans. Signal Process., 2021

Communication-Adaptive Stochastic Gradient Methods for Distributed Learning.
IEEE Trans. Signal Process., 2021

Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances.
SIAM J. Sci. Comput., 2021

Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures.
J. Sci. Comput., 2021

A Novel Convergence Analysis for Algorithms of the Adam Family.
CoRR, 2021

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning.
CoRR, 2021

Curvature-Aware Derivative-Free Optimization.
CoRR, 2021

Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems.
CoRR, 2021

Learn to Predict Equilibria via Fixed Point Networks.
CoRR, 2021

On Stochastic Moving-Average Estimators for Non-Convex Optimization.
CoRR, 2021

Feasibility-based Fixed Point Networks.
CoRR, 2021

On the Comparison between Cyclic Sampling and Random Reshuffling.
CoRR, 2021

Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop.
CoRR, 2021

A Single-Timescale Stochastic Bilevel Optimization Method.
CoRR, 2021

Exponential Graph is Provably Efficient for Decentralized Deep Training.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hyperparameter Tuning is All You Need for LISTA.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AutoBandit: A Meta Bandit Online Learning System.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Provably Correct Optimization and Exploration with Non-linear Policies.
Proceedings of the 38th International Conference on Machine Learning, 2021

Accelerating Gossip SGD with Periodic Global Averaging.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning A Minimax Optimizer: A Pilot Study.
Proceedings of the 9th International Conference on Learning Representations, 2021

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

An Optimal Stochastic Compositional Optimization Method with Applications to Meta Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

CADA: Communication-Adaptive Distributed Adam.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization.
IEEE Trans. Signal Process., 2020

Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters.
IEEE Trans. Signal Process., 2020

Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers.
IEEE Trans. Neural Networks Learn. Syst., 2020

Hybrid Federated Learning: Algorithms and Implementation.
CoRR, 2020

Attentional Biased Stochastic Gradient for Imbalanced Classification.
CoRR, 2020

SCOBO: Sparsity-Aware Comparison Oracle Based Optimization.
CoRR, 2020

Projecting to Manifolds via Unsupervised Learning.
CoRR, 2020

VAFL: a Method of Vertical Asynchronous Federated Learning.
CoRR, 2020

FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data.
CoRR, 2020

Provably Efficient Exploration for RL with Unsupervised Learning.
CoRR, 2020

LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning.
CoRR, 2020

Scaled Relative Graph of Normal Matrices.
CoRR, 2020

Markov chain block coordinate descent.
Comput. Optim. Appl., 2020

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

An Improved Analysis of Stochastic Gradient Descent with Momentum.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Consistent Dynamic Mode Decomposition.
SIAM J. Appl. Dyn. Syst., 2019

Denoising Prior Driven Deep Neural Network for Image Restoration.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

A new use of Douglas-Rachford splitting for identifying infeasible, unbounded, and pathological conic programs.
Math. Program., 2019

Run-and-Inspect Method for nonconvex optimization and global optimality bounds for R-local minimizers.
Math. Program., 2019

Global Convergence of ADMM in Nonconvex Nonsmooth Optimization.
J. Sci. Comput., 2019

Algorithm for Hamilton-Jacobi Equations in Density Space Via a Generalized Hopf Formula.
J. Sci. Comput., 2019

An Envelope for Davis-Yin Splitting and Strict Saddle-Point Avoidance.
J. Optim. Theory Appl., 2019

Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning.
J. Mach. Learn. Res., 2019

Algorithm for overcoming the curse of dimensionality for state-dependent Hamilton-Jacobi equations.
J. Comput. Phys., 2019

Walk Proximal Gradient: An Energy-Efficient Algorithm for Consensus Optimization.
IEEE Internet Things J., 2019

Does Knowledge Transfer Always Help to Learn a Better Policy?
CoRR, 2019

XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training.
CoRR, 2019

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs.
CoRR, 2019

Douglas-Rachford splitting and ADMM for pathological convex optimization.
Comput. Optim. Appl., 2019

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers.
Proceedings of the 36th International Conference on Machine Learning, 2019

Acceleration of SVRG and Katyusha X by Inexact Preconditioning.
Proceedings of the 36th International Conference on Machine Learning, 2019

ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA.
Proceedings of the 7th International Conference on Learning Representations, 2019

A2BCD: Asynchronous Acceleration with Optimal Complexity.
Proceedings of the 7th International Conference on Learning Representations, 2019

On the Comparison between Primal and Primal-dual Methods in Decentralized Dynamic Optimization.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
A Distributed ADMM Approach With Decomposition-Coordination for Mobile Data Offloading.
IEEE Trans. Veh. Technol., 2018

On Nonconvex Decentralized Gradient Descent.
IEEE Trans. Signal Process., 2018

Decentralized Consensus Optimization With Asynchrony and Delays.
IEEE Trans. Signal Inf. Process. over Networks, 2018

Learning Collaborative Sparsity Structure via Nonconvex Optimization for Feature Recognition.
IEEE Trans. Ind. Informatics, 2018

A Fast and Accurate Basis Pursuit Denoising Algorithm With Application to Super-Resolving Tomographic SAR.
IEEE Trans. Geosci. Remote. Sens., 2018

First- and Second-Order Methods for Online Convolutional Dictionary Learning.
SIAM J. Imaging Sci., 2018

Cauchy Noise Removal by Nonconvex ADMM with Convergence Guarantees.
J. Sci. Comput., 2018

A Parallel Method for Earth Mover's Distance.
J. Sci. Comput., 2018

On Unbounded Delays in Asynchronous Parallel Fixed-Point Algorithms.
J. Sci. Comput., 2018

Parallel redistancing using the Hopf-Lax formula.
J. Comput. Phys., 2018

AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Reinforcement Learning with Near-Optimal Sample Complexity.
CoRR, 2018

Markov Chain Block Coordinate Descent.
CoRR, 2018

A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization.
CoRR, 2018

On Markov Chain Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Breaking the Span Assumption Yields Fast Finite-Sum Minimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Cyclic Coordinate-Update Algorithms for Fixed-Point Problems: Analysis and Applications.
SIAM J. Sci. Comput., 2017

Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions.
Math. Oper. Res., 2017

A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update.
J. Sci. Comput., 2017

Parallel Multi-Block ADMM with o(1 / k) Convergence.
J. Sci. Comput., 2017

Algorithm for Overcoming the Curse of Dimensionality For Time-Dependent Non-convex Hamilton-Jacobi Equations Arising From Optimal Control and Differential Games Problems.
J. Sci. Comput., 2017

More Iterations per Second, Same Quality - Why Asynchronous Algorithms may Drastically Outperform Traditional Ones.
CoRR, 2017

A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs.
CoRR, 2017

Asynchronous Coordinate Descent under More Realistic Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Straggler Mitigation in Distributed Optimization Through Data Encoding.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Accelerated high-resolution EEG source imaging.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

Robust linear unmixing with enhanced sparsity.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Online convolutional dictionary learning.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Decentralized bundle method for nonsmooth consensus optimization.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016
ARock: An Algorithmic Framework for Asynchronous Parallel Coordinate Updates.
SIAM J. Sci. Comput., 2016

On the Convergence of Decentralized Gradient Descent.
SIAM J. Optim., 2016

On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers.
J. Sci. Comput., 2016

On the Convergence of Asynchronous Parallel Iteration with Arbitrary Delays.
CoRR, 2016

Coordinate Friendly Structures, Algorithms and Applications.
CoRR, 2016

One condition for solution uniqueness and robustness of both l1-synthesis and l1-analysis minimizations.
Adv. Comput. Math., 2016

Expander graph and communication-efficient decentralized optimization.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
A Proximal Gradient Algorithm for Decentralized Composite Optimization.
IEEE Trans. Signal Process., 2015

NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings.
IEEE Trans. Signal Process., 2015

Sparse kernel learning-based feature selection for anomaly detection.
IEEE Trans. Aerosp. Electron. Syst., 2015

Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization.
SIAM J. Optim., 2015

EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization.
SIAM J. Optim., 2015

Necessary and Sufficient Conditions of Solution Uniqueness in 1-Norm Minimization.
J. Optim. Theory Appl., 2015

ExtraPush for Convex Smooth Decentralized Optimization over Directed Networks.
CoRR, 2015

A proximal gradient algorithm for decentralized nondifferentiable optimization.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Prediction of High Resolution Spatial-Temporal Air Pollutant Map from Big Data Sources.
Proceedings of the Big Data Computing and Communications - First International Conference, 2015

2014
On the Linear Convergence of the ADMM in Decentralized Consensus Optimization.
IEEE Trans. Signal Process., 2014

A New Detail-Preserving Regularization Scheme.
SIAM J. Imaging Sci., 2014

Folding-Free Global Conformal Mapping for Genus-0 Surfaces by Harmonic Energy Minimization.
J. Sci. Comput., 2014

A fast patch-dictionary method for whole image recovery.
CoRR, 2014

Democratic Representations.
CoRR, 2014

Video Compressive Sensing for Dynamic MRI.
CoRR, 2014

2013
Decentralized Jointly Sparse Optimization by Reweighted l<sub>q</sub> Minimization.
IEEE Trans. Signal Process., 2013

Improved Iteratively Reweighted Least Squares for Unconstrained Smoothed 퓁<sub>q</sub> Minimization.
SIAM J. Numer. Anal., 2013

A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion.
SIAM J. Imaging Sci., 2013

Augmented 퓁<sub>1</sub> and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm.
SIAM J. Imaging Sci., 2013

A feasible method for optimization with orthogonality constraints.
Math. Program., 2013

Error Forgetting of Bregman Iteration.
J. Sci. Comput., 2013

One condition for all: solution uniqueness and robustness of ℓ<sub>1</sub>-synthesis and ℓ<sub>1</sub>-analysis minimizations
CoRR, 2013

Gradient methods for convex minimization: better rates under weaker conditions
CoRR, 2013

A dual algorithm for a class of augmented convex models.
CoRR, 2013

Parallel matrix factorization for low-rank tensor completion.
CoRR, 2013

An efficient augmented Lagrangian method with applications to total variation minimization.
Comput. Optim. Appl., 2013

Optimal sparse kernel learning for hyperspectral anomaly detection.
Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2013

A distribute parallel approach for big data scale optimal power flow with security constraints.
Proceedings of the IEEE Fourth International Conference on Smart Grid Communications, 2013

Linearly convergent decentralized consensus optimization with the alternating direction method of multipliers.
Proceedings of the IEEE International Conference on Acoustics, 2013

A linearized bregman algorithm for decentralized basis pursuit.
Proceedings of the 21st European Signal Processing Conference, 2013

Mixing space-time derivatives for video compressive sensing.
Proceedings of the 2013 Asilomar Conference on Signals, 2013

Parallel and distributed sparse optimization.
Proceedings of the 2013 Asilomar Conference on Signals, 2013

2012
Edge Guided Reconstruction for Compressive Imaging.
SIAM J. Imaging Sci., 2012

Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging.
SIAM J. Imaging Sci., 2012

On the convergence of an active-set method for ℓ<sub>1</sub> minimization.
Optim. Methods Softw., 2012

Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm.
Math. Program. Comput., 2012

Compressive Sensing Based High-Resolution Channel Estimation for OFDM System.
IEEE J. Sel. Top. Signal Process., 2012

A multi-block alternating direction method with parallel splitting for decentralized consensus optimization.
EURASIP J. Wirel. Commun. Netw., 2012

Copula density estimation by total variation penalized likelihood with linear equality constraints.
Comput. Stat. Data Anal., 2012

Necessary and sufficient conditions of solution uniqueness in ℓ<sub>1</sub> minimization
CoRR, 2012

Augmented L1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm
CoRR, 2012

Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Decentralized low-rank matrix completion.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Signal representations with minimum ℓ∞-norm.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011
Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements.
IEEE Trans. Signal Process., 2011

Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks.
IEEE J. Sel. Areas Commun., 2011

Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising
CoRR, 2011

An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors
CoRR, 2011

High Resolution OFDM Channel Estimation with Low Speed ADC Using Compressive Sensing.
Proceedings of IEEE International Conference on Communications, 2011

Oil spill sensor using multispectral infrared imaging via ℓ1 minimization.
Proceedings of the IEEE International Conference on Acoustics, 2011

Dynamic compressive spectrum sensing for cognitive radio networks.
Proceedings of the 45st Annual Conference on Information Sciences and Systems, 2011

2010
Image-based face illumination transferring using logarithmic total variation models.
Vis. Comput., 2010

A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation.
SIAM J. Sci. Comput., 2010

Analysis and Generalizations of the Linearized Bregman Method.
SIAM J. Imaging Sci., 2010

Sparse Signal Reconstruction via Iterative Support Detection.
SIAM J. Imaging Sci., 2010

Alternating direction augmented Lagrangian methods for semidefinite programming.
Math. Program. Comput., 2010

A Fast Alternating Direction Method for TVL1-L2 Signal Reconstruction From Partial Fourier Data.
IEEE J. Sel. Top. Signal Process., 2010

A Fast Hybrid Algorithm for Large-Scale <i>l<sub>1</sub></i>-Regularized Logistic Regression.
J. Mach. Learn. Res., 2010

Practical compressive sensing with Toeplitz and circulant matrices.
Proceedings of the Visual Communications and Image Processing 2010, 2010

EdgeCS: edge guided compressive sensing reconstruction.
Proceedings of the Visual Communications and Image Processing 2010, 2010

Collaborative spectrum sensing from sparse observations using matrix completion for cognitive radio networks.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise.
SIAM J. Sci. Comput., 2009

Parametric Maximum Flow Algorithms for Fast Total Variation Minimization.
SIAM J. Sci. Comput., 2009

A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration.
SIAM J. Imaging Sci., 2009

A Curvilinear Search Method for p-Harmonic Flows on Spheres.
SIAM J. Imaging Sci., 2009

Compressed Sensing via Iterative Support Detection
CoRR, 2009

2008
Fixed-Point Continuation for l<sub>1</sub>-Minimization: Methodology and Convergence.
SIAM J. Optim., 2008

Bregman Iterative Algorithms for \ell<sub>1</sub>-Minimization with Applications to Compressed Sensing.
SIAM J. Imaging Sci., 2008

A New Alternating Minimization Algorithm for Total Variation Image Reconstruction.
SIAM J. Imaging Sci., 2008

A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents
CoRR, 2008

Iteratively reweighted algorithms for compressive sensing.
Proceedings of the IEEE International Conference on Acoustics, 2008

An efficient algorithm for compressed MR imaging using total variation and wavelets.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
The Total Variation Regularized L<sup>1</sup> Model for Multiscale Decomposition.
Multiscale Model. Simul., 2007

A comparison of three total variation based texture extraction models.
J. Vis. Commun. Image Represent., 2007

2006
Total Variation Models for Variable Lighting Face Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

2005
Second-order Cone Programming Methods for Total Variation-Based Image Restoration.
SIAM J. Sci. Comput., 2005

An Iterative Regularization Method for Total Variation-Based Image Restoration.
Multiscale Model. Simul., 2005

Background correction for cDNA microarray images using the TV+<i>L</i><sup>1</sup> model.
Bioinform., 2005

Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L<sup>1</sup> Functional.
Proceedings of the Variational, 2005

Illumination Normalization for Face Recognition and Uneven Background Correction Using Total Variation Based Image Models.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

A New Coarse-to-Fine Framework for 3D Brain MR Image Registration.
Proceedings of the Computer Vision for Biomedical Image Applications, 2005


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