Wotao Yin

Q: What Schools Are Affiliated With Wotao Yin

Wotao Yin is affiliated with the following schools: Rice University, University of Science and Technology of China, Nanjing University, University of California, Los Angeles, Stanford University, Columbia University

Wotao Yin's AcademicInfluence.com Rankings

Wotao Yin

Mathematics

#3567

World Rank

#5242

Historical Rank

Applied Mathematics

#124

World Rank

#139

Historical Rank

Measure Theory

#680

World Rank

#925

Historical Rank

mathematics Degrees

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Mathematics

Wotao Yin's Degrees

PhD Mathematics Stanford University
Masters Mathematics Stanford University
Bachelors Mathematics University of Science and Technology of China

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Why Is Wotao Yin Influential?

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According to Wikipedia, Wotao Yin is an applied mathematician and professor of Mathematics department at the University of California, Los Angeles in Los Angeles, California. He currently conducts research in optimization, parallel and distributed computing, and inverse problems.

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Wotao Yin's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

A New Alternating Minimization Algorithm for Total Variation Image Reconstruction (2008) (1849)
An Iterative Regularization Method for Total Variation-Based Image Restoration (2005) (1824)
Bregman Iterative Algorithms for \ell1-Minimization with Applications to Compressed Sensing (2008) (1499)
Iteratively reweighted algorithms for compressive sensing (2008) (1270)
A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion (2013) (979)
EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization (2014) (948)
Fixed-Point Continuation for l1-Minimization: Methodology and Convergence (2008) (892)
Global Convergence of ADMM in Nonconvex Nonsmooth Optimization (2015) (838)
A feasible method for optimization with orthogonality constraints (2013) (800)
Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm (2012) (715)
On the Linear Convergence of the ADMM in Decentralized Consensus Optimization (2013) (691)
On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers (2016) (645)
A Fast Alternating Direction Method for TVL1-L2 Signal Reconstruction From Partial Fourier Data (2010) (563)
On the Convergence of Decentralized Gradient Descent (2013) (522)
Total variation models for variable lighting face recognition (2006) (503)
A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration (2009) (485)
An efficient augmented Lagrangian method with applications to total variation minimization (2013) (468)
Learning to Optimize (2008) (410)
Alternating direction augmented Lagrangian methods for semidefinite programming (2010) (403)
Parallel Multi-Block ADMM with o(1 / k) Convergence (2013) (397)
An efficient algorithm for compressed MR imaging using total variation and wavelets (2008) (383)
An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise (2009) (359)
Improved Iteratively Reweighted Least Squares for Unconstrained Smoothed 퓁q Minimization (2013) (347)
An alternating direction algorithm for matrix completion with nonnegative factors (2011) (322)
A Three-Operator Splitting Scheme and its Optimization Applications (2015) (309)
Parallel matrix factorization for low-rank tensor completion (2013) (294)
Group sparse optimization by alternating direction method (2013) (288)
Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising (2011) (286)
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation (2010) (280)
Denoising Prior Driven Deep Neural Network for Image Restoration (2018) (262)
A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update (2014) (247)
Sparse Signal Reconstruction via Iterative Support Detection (2009) (243)
Convergence Rate Analysis of Several Splitting Schemes (2014) (242)
ARock: an Algorithmic Framework for Asynchronous Parallel Coordinate Updates (2015) (239)
Second-order Cone Programming Methods for Total Variation-Based Image Restoration (2005) (220)
A Proximal Gradient Algorithm for Decentralized Composite Optimization (2015) (220)
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning (2018) (218)
Analysis and Generalizations of the Linearized Bregman Method (2010) (203)
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers (2019) (201)
User’s Guide for TVAL3: TV Minimization by Augmented Lagrangian and Alternating Direction Algorithms (2010) (181)
A Fast Algorithm for Image Deblurring with Total Variation Regularization (2007) (180)
Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks (2010) (179)
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds (2018) (171)
Practical compressive sensing with Toeplitz and circulant matrices (2010) (169)
Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements (2011) (168)
A New Detail-Preserving Regularization Scheme (2014) (151)
Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions (2014) (149)
Splitting Methods in Communication, Imaging, Science, and Engineering (2017) (144)
Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L1 Functional (2005) (135)
On Nonconvex Decentralized Gradient Descent (2016) (133)
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA (2018) (127)
Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization (2014) (122)
Straggler Mitigation in Distributed Optimization Through Data Encoding (2017) (122)
The Total Variation Regularized L1 Model for Multiscale Decomposition (2007) (120)
TR 0707 A Fixed-Point Continuation Method for ` 1-Regularized Minimization with Applications to Compressed Sensing (2007) (117)
Parametric Maximum Flow Algorithms for Fast Total Variation Minimization (2009) (115)
Augmented 퓁1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm (2012) (110)
Illumination normalization for face recognition and uneven background correction using total variation based image models (2005) (108)
Decentralized Consensus Optimization With Asynchrony and Delays (2016) (97)
Parallel and distributed sparse optimization (2013) (96)
Compressive Sensing Based High-Resolution Channel Estimation for OFDM System (2012) (94)
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data (2020) (86)
A Fixed-Point Continuation Method for L_1-Regularization with Application to Compressed Sensing (2007) (85)
Learning to Optimize: A Primer and A Benchmark (2021) (82)
NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings (2015) (78)
A Parallel Method for Earth Mover’s Distance (2018) (77)
VAFL: a Method of Vertical Asynchronous Federated Learning (2020) (75)
Coordinate Friendly Structures, Algorithms and Applications (2016) (74)
An Improved Analysis of Stochastic Gradient Descent with Momentum (2020) (74)
Background correction for cDNA microarray images using the TV+L1 model (2005) (74)
A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression (2010) (72)
Gradient methods for convex minimization: better rates under weaker conditions (2013) (72)
Error Forgetting of Bregman Iteration (2013) (72)
A comparison of three total variation based texture extraction models (2007) (70)
Necessary and Sufficient Conditions of Solution Uniqueness in 1-Norm Minimization (2012) (69)
Cauchy Noise Removal by Nonconvex ADMM with Convergence Guarantees (2018) (69)
ExtraPush for Convex Smooth Decentralized Optimization over Directed Networks (2015) (69)
Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging (2012) (68)
Decentralized low-rank matrix completion (2012) (67)
Self Equivalence of the Alternating Direction Method of Multipliers (2014) (67)
A Primer on Coordinate Descent Algorithms (2016) (67)
On the convergence of an active-set method for ℓ1 minimization (2012) (65)
A Fast TVL1-L2 Minimization Algorithm for Signal Reconstruction from Partial Fourier Data (2008) (64)
FIXED-POINT CONTINUATION APPLIED TO COMPRESSED SENSING: IMPLEMENTATION AND NUMERICAL EXPERIMENTS * (2010) (64)
Compressive Sensing for Wireless Networks (2013) (63)
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods (2022) (61)
A rapid and robust numerical algorithm for sensitivity encoding with sparsity constraints: Self‐feeding sparse SENSE (2010) (58)
Edge Guided Reconstruction for Compressive Imaging (2012) (58)
Asynchronous Coordinate Descent under More Realistic Assumptions (2017) (58)
EdgeCS: edge guided compressive sensing reconstruction (2010) (58)
Collaborative spectrum sensing from sparse observations using matrix completion for cognitive radio networks (2010) (57)
MR image reconstruction using deep learning: evaluation of network structure and loss functions. (2019) (56)
A Single-Timescale Stochastic Bilevel Optimization Method (2021) (56)
Algorithm for overcoming the curse of dimensionality for state-dependent Hamilton-Jacobi equations (2017) (56)
A fast patch-dictionary method for whole image recovery (2014) (56)
On Markov Chain Gradient Descent (2018) (55)
A Curvilinear Search Method for p-Harmonic Flows on Spheres (2009) (54)
Sparse Recovery via Differential Inclusions (2014) (53)
On Unbounded Delays in Asynchronous Parallel Fixed-Point Algorithms (2016) (52)
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization (2020) (49)
Democratic Representations (2014) (47)
Folding-Free Global Conformal Mapping for Genus-0 Surfaces by Harmonic Energy Minimization (2014) (47)
One condition for solution uniqueness and robustness of both l1-synthesis and l1-analysis minimizations (2013) (47)
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning (2018) (45)
Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers (2020) (45)
On Stochastic Moving-Average Estimators for Non-Convex Optimization (2021) (45)
Extracting respiratory signals from thoracic cone beam CT projections (2012) (44)
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems (2021) (43)
Decentralized Jointly Sparse Optimization by Reweighted $\ell_{q}$ Minimization (2013) (42)
Algorithm for Overcoming the Curse of Dimensionality For Time-Dependent Non-convex Hamilton–Jacobi Equations Arising From Optimal Control and Differential Games Problems (2017) (41)
Image-based face illumination transferring using logarithmic total variation models (2009) (39)
Signal representations with minimum ℓ∞-norm (2012) (38)
Compressive Sensing for Wireless Networks: Preface (2013) (37)
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data (2020) (37)
Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization (2018) (36)
Total Variation Based Image Cartoon-Texture Decomposition (2005) (36)
Compressive Sensing for Wireless Networks: Compressive Sensing Technique (2013) (35)
Consistent Dynamic Mode Decomposition (2019) (34)
Compressed Sensing via Iterative Support Detection (2009) (33)
Compressive Sensing for Wireless Networks by Zhu Han (2013) (33)
A Sharp Convergence Rate Analysis for Distributed Accelerated Gradient Methods (2018) (31)
Copula Density Estimation by Total Variation Penalized Likelihood (2009) (30)
USING GEOMETRY AND ITERATED REFINEMENT FOR INVERSE PROBLEMS (1): TOTAL VARIATION BASED IMAGE RESTORATION (2004) (29)
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs (2019) (28)
Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances (2018) (28)
Exponential Graph is Provably Efficient for Decentralized Deep Training (2021) (28)
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters (2018) (27)
Dynamic compressive spectrum sensing for cognitive radio networks (2011) (26)
Cyclic Coordinate-Update Algorithms for Fixed-Point Problems: Analysis and Applications (2016) (26)
Algorithm for overcoming the curse of dimensionality for certain non-convex Hamilton–Jacobi equations, projections and differential games (2018) (26)
On the o(1/k) Convergence and Parallelization of the Alternating Direction Method of Multipliers (2013) (25)
IMPROVED ITERATIVELY REWEIGHTED LEAST SQUARES FOR UNCONSTRAINED (2013) (25)
JFB: Jacobian-Free Backpropagation for Implicit Networks (2021) (25)
Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry (2019) (25)
Acceleration of Primal–Dual Methods by Preconditioning and Simple Subproblem Procedures (2018) (25)
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling (2020) (24)
On the Convergence of Asynchronous Parallel Iteration with Unbounded Delays (2016) (24)
XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training (2019) (24)
Online convolutional dictionary learning (2017) (24)
Decentralized Jointly Sparse Optimization by Reweighted Minimization (2013) (23)
Proximal-Proximal-Gradient Method (2017) (23)
Expander graph and communication-efficient decentralized optimization (2016) (23)
A new use of Douglas–Rachford splitting for identifying infeasible, unbounded, and pathological conic programs (2019) (22)
Algorithm for Hamilton–Jacobi Equations in Density Space Via a Generalized Hopf Formula (2018) (22)
A distribute parallel approach for big data scale optimal power flow with security constraints (2013) (22)
A Single-Timescale Method for Stochastic Bilevel Optimization (2021) (21)
A Fast and Accurate Basis Pursuit Denoising Algorithm With Application to Super-Resolving Tomographic SAR (2018) (21)
A Novel Convergence Analysis for Algorithms of the Adam Family (2021) (20)
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training (2021) (20)
On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers (2015) (20)
Nonconvex Sparse Regularization and Splitting Algorithms (2016) (19)
Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging. (2019) (19)
A New Coarse-to-Fine Framework for 3D Brain MR Image Registration (2005) (19)
Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop (2021) (19)
Learning A Minimax Optimizer: A Pilot Study (2021) (18)
Accelerating Gossip SGD with Periodic Global Averaging (2021) (17)
On the Convergence of Asynchronous Parallel Iteration with Arbitrary Delays (2016) (17)
Walk Proximal Gradient: An Energy-Efficient Algorithm for Consensus Optimization (2019) (17)
More Iterations per Second, Same Quality - Why Asynchronous Algorithms may Drastically Outperform Traditional Ones (2017) (17)
Video compressive sensing for dynamic MRI (2012) (16)
Learning Circulant Sensing Kernels (2014) (16)
Extracting Salient Features From Less Data via ! 1 -Minimization (2008) (16)
A linearized bregman algorithm for decentralized basis pursuit (2013) (16)
A2BCD: Asynchronous Acceleration with Optimal Complexity (2018) (16)
Sparse kernel learning-based feature selection for anomaly detection (2015) (16)
Learning Collaborative Sparsity Structure via Nonconvex Optimization for Feature Recognition (2018) (16)
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection (2021) (15)
Feasibility-based fixed point networks (2021) (15)
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems (2021) (15)
A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs (2017) (15)
Douglas–Rachford splitting and ADMM for pathological convex optimization (2018) (15)
Linearly convergent decentralized consensus optimization with the alternating direction method of multipliers (2013) (14)
Tight coefficients of averaged operators via scaled relative graph (2019) (14)
Learn to Predict Equilibria via Fixed Point Networks (2021) (14)
CADA: Communication-Adaptive Distributed Adam (2020) (13)
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization (2021) (13)
Breaking the Span Assumption Yields Fast Finite-Sum Minimization (2018) (13)
Slope and $G$-set characterization of set-valued functions and applications to non-differentiable optimization problems (2005) (13)
A2BCD: An Asynchronous Accelerated Block Coordinate Descent Algorithm With Optimal Complexity (2018) (13)
Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints (2021) (12)
An Envelope for Davis–Yin Splitting and Strict Saddle-Point Avoidance (2018) (12)
A Distributed ADMM Approach With Decomposition-Coordination for Mobile Data Offloading (2018) (12)
Safeguarded Learned Convex Optimization (2020) (11)
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning (2021) (10)
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning (2020) (10)
A proximal gradient algorithm for decentralized nondifferentiable optimization (2015) (10)
Wasserstein-Based Projections with Applications to Inverse Problems (2022) (10)
Scaled Relative Graph of Normal Matrices (2019) (10)
High Resolution OFDM Channel Estimation with Low Speed ADC Using Compressive Sensing (2011) (10)
TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods (2016) (10)
LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning (2020) (10)
Parallel Multi-Block ADMM with o(1 / k) Convergence (2016) (9)
Decentralized Learning With Lazy and Approximate Dual Gradients (2020) (9)
An efficient augmented Lagrangian method with applications to total variation minimization (2013) (9)
Necessary and sufficient conditions of solution uniqueness in ℓ1 minimization (2012) (9)
A One-bit, Comparison-Based Gradient Estimator (2020) (9)
A dual algorithm for a class of augmented convex signal recovery models (2015) (8)
Hyperparameter Tuning is All You Need for LISTA (2021) (8)
Attentional Biased Stochastic Gradient for Imbalanced Classification (2020) (8)
Parallel redistancing using the Hopf-Lax formula (2018) (8)
Compressive Sensing for Wireless Networks: Sparse optimization algorithms (2013) (8)
Provably Correct Optimization and Exploration with Non-linear Policies (2021) (7)
Markov chain block coordinate descent (2018) (7)
From the simplex to the sphere: Faster constrained optimization using the Hadamard parametrization (2021) (7)
Provably Efficient Exploration for RL with Unsupervised Learning (2020) (7)
Large-Scale Convex Optimization (2022) (7)
Prediction of High Resolution Spatial-Temporal Air Pollutant Map from Big Data Sources (2015) (6)
A Mean Field Game Inverse Problem (2020) (6)
Hybrid Federated Learning: Algorithms and Implementation (2020) (6)
Augmented l1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm. Revision 1 (2012) (6)
Efficient simultaneous image deconvolution and upsampling algorithm for low-resolution microwave sounder data (2015) (6)
HYPERSPECTRAL DATA RECONSTRUCTION COMBINING SPATIAL AND SPECTRAL SPARSITY (2010) (6)
How Does an Approximate Model Help in Reinforcement Learning (2019) (5)
Fast non-coplanar beam orientation optimization based on group sparsity (2017) (5)
A New Regularization Path for Logistic Regression via Linearized Bregman (2012) (5)
Communication-Adaptive Stochastic Gradient Methods for Distributed Learning (2021) (5)
Decentralized Consensus Optimization with Asynchrony and Delay (2016) (5)
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression (2022) (5)
On the geometric analysis of a quartic–quadratic optimization problem under a spherical constraint (2019) (5)
Sparse Recovery via l1 and L1 Optimization (2014) (5)
Acceleration of SVRG and Katyusha X by Inexact Preconditioning (2019) (4)
A dual algorithm for a class of augmented convex models (2013) (4)
Signal Representation with Minimum L_Infinity Norm (2012) (4)
Curvature-Aware Derivative-Free Optimization (2021) (4)
An alternating direction algorithm for matrix completion with nonnegative factors (2012) (4)
A Multiscale Semi-Smooth Newton Method for Optimal Transport (2022) (4)
Internally Induced Branch-and-Cut Acceleration for Unit Commitment Based on Improvement of Upper Bound (2022) (4)
A multi-block alternating direction method with parallel splitting for decentralized consensus optimization (2012) (4)
Douglas-Rachford Splitting for Pathological Convex Optimization (2018) (3)
Linearized Bregman for l 1-regularized Logistic Regression (2013) (3)
Oil spill sensor using multispectral infrared imaging via ℓ1 minimization (2011) (3)
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders (2021) (3)
One condition for all: solution uniqueness and robustness of ℓ1-synthesis and ℓ1-analysis minimizations (2013) (3)
Does Knowledge Transfer Always Help to Learn a Better Policy? (2019) (3)
Robust linear unmixing with enhanced sparsity (2017) (3)
Mixing space-time derivatives for video compressive sensing (2013) (3)
Run-and-Inspect Method for nonconvex optimization and global optimality bounds for R-local minimizers (2017) (3)
FAST AND ROBUST ALGORITHMS FOR HARMONIC ENERGY MINIMIZATION ON GENUS-0 SURFACES (2011) (2)
TH-EF-BRB-05: 4pi Non-Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty. (2016) (2)
Projecting to Manifolds via Unsupervised Learning (2020) (2)
Optimal sparse kernel learning for hyperspectral anomaly detection (2013) (2)
AS A MATLAB Solver for l 1-Regularized Least Squares Problems (2008) (2)
Decentralized bundle method for nonsmooth consensus optimization (2017) (2)
Accelerated high-resolution EEG source imaging (2017) (2)
Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization (2022) (2)
On the Comparison between Cyclic Sampling and Random Reshuffling (2021) (2)
Algorithm for Overcoming the Curse of Dimensionality For Time-Dependent Non-convex Hamilton–Jacobi Equations Arising From Optimal Control and Differential Games Problems (2017) (2)
Compressive Sensing for Wireless Networks: Positioning (2013) (2)
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity (2018) (2)
Scaled Relative Graph (2019) (2)
An Optimal Stochastic Compositional Optimization Method with Applications to Meta Learning (2021) (1)
On Nonconvex Decentralized Gradient Descent Jinshan Zeng , and Wotao Yin (2016) (1)
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Reinforcement Learning with Near-Optimal Sample Complexity (2018) (1)
Compressive Sensing for Wireless Networks: Compressive sensing framework (2013) (1)
ARock : an Algorithmic Framework for Async-Parallel Coordinate Updates (2015) (1)
On the Convergence of Asynchronous Parallel Iteration with Unbounded Delays (2017) (1)
On Representing Linear Programs by Graph Neural Networks (2022) (1)
A Three-Operator Splitting Scheme and its Optimization Applications (2017) (1)
Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models (2012) (1)
Compressed channel estimation (2013) (1)
On the Comparison between Primal and Primal-dual Methods in Decentralized Dynamic Optimization (2019) (1)
Necessary and Sufficient Conditions of Solution Uniqueness in l(sub 1) Minimization (Preprint) (2012) (1)
Acceleration of Primal-Dual Methods by Preconditioning and Fixed Number of Inner Loops (2018) (1)
Noisy Sparsity Recovery via Differential Equations (2014) (1)
Preface (2015) (0)
A new use of Douglas–Rachford splitting for identifying infeasible, unbounded, and pathological conic programs (2018) (0)
Compressive Hyperspectral Imaging and Anomaly Detection (2013) (0)
Compressive Sensing for Wireless Networks: Introduction (2013) (0)
Compressive Sensing for Wireless Networks: Cognitive radio networks (2013) (0)
Supplementary materials for “ CADA : Communication-Adaptive Distributed Adam " (2021) (0)
Correction to: On the Convergence of Asynchronous Parallel Iteration with Unbounded Delays (2016) (0)
Markov chain block coordinate descent (2019) (0)
Compressive Sensing for Wireless Networks: Overview of wireless networks (2013) (0)
Sparse Radon transform with dual gradient ascent method (2013) (0)
Error Forgetting of Bregman Iteration (2012) (0)
Attentional-Biased Stochastic Gradient Descent (2020) (0)
Folding-Free Global Conformal Mapping for Genus-0 Surfaces by Harmonic Energy Minimization (2013) (0)
SCOBO: Sparsity-Aware Comparison Oracle Based Optimization (2020) (0)
Real-time Sequential Security-Constrained Optimal Power Flow: A Hybrid Knowledge-Data-Driven Reinforcement Learning Approach (2023) (0)
On Unbounded Delays in Asynchronous Parallel Fixed-Point Algorithms (2017) (0)
Compressive Sensing for Wireless Networks: Ultra-wideband systems (2013) (0)
FAST COMMUNICATION HIERARCHICAL LOW-RANK STRUCTURE OF PARAMETERIZED DISTRIBUTIONS∗ (2021) (0)
Decomposition Methods for Global Solutions of Mixed-Integer Linear Programs (2021) (0)
TU‐C‐213CD‐12: Respiratory Signal Extraction from Thoracic Cone Beam CT Projections (2012) (0)
An Envelope for Davis–Yin Splitting and Strict Saddle-Point Avoidance (2019) (0)
Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate (2022) (0)
Algorithm for Hamilton–Jacobi Equations in Density Space Via a Generalized Hopf Formula (2019) (0)
Sparsity Recovery via Differential Equations (2014) (0)
A Parallel Method for Earth Mover’s Distance (2017) (0)
Run-and-Inspect Method for nonconvex optimization and global optimality bounds for R-local minimizers (2019) (0)
Compressive Sensing for Wireless Networks: CS analog-to-digital converter (2013) (0)
On Representing Mixed-Integer Linear Programs by Graph Neural Networks (2022) (0)
Cauchy Noise Removal by Nonconvex ADMM with Convergence Guarantees (2017) (0)
A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update (2017) (0)
Global Convergence of ADMM in Nonconvex Nonsmooth Optimization (2018) (0)
AutoBandit: A Meta Bandit Online Learning System (2021) (0)
Universal Safeguarded Learned Convex Optimization with Guaranteed Convergence (2019) (0)
A feasible method for optimization with orthogonality constraints (2012) (0)
A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents (2008) (0)
The tv-l(1) model: theory, computation, and applications (2006) (0)
TR 0710 A Fast Algorithm for Image Deblurring with Total Variation Regularization (2007) (0)
Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry (2021) (0)
An efficient algorithm for compressive sensing based SAR tomography (2018) (0)
Necessary and Sufficient Conditions of Solution Uniqueness in 1-Norm Minimization (2014) (0)
GROUP SPARSE OPTIMIZATION BY ALTERNATING DIRECTION METHOD Report Title (2012) (0)
One condition for solution uniqueness and robustness of both l1-synthesis and l1-analysis minimizations (2016) (0)
Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints (2022) (0)
One condition for all: solution uniqueness and robustness of $\ell_1$-synthesis and $\ell_1$-analysis minimizations (2013) (0)

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