UB Paderborn / Katalog / Suche / in CDI

Sparse Approximation via Penalty Decomposition Methods

SIAM journal on optimization, 2013-01, Vol.23 (4), p.2448-2478

2013

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Smooth Optimization Approach for Sparse Covariance Selection

SIAM journal on optimization, 2009-01, Vol.19 (4), p.1807-1827

Lu, Zhaosong

2009

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Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming

SIAM journal on optimization, 2019-01, Vol.29 (4), p.2725-2752

2019

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An augmented Lagrangian approach for sparse principal component analysis

Mathematical programming, 2012-10, Vol.135 (1-2), p.149-193

2012

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Sparse Recovery via Partial Regularization: Models, Theory, and Algorithms

Mathematics of operations research, 2018-11, Vol.43 (4), p.1290-1316

2018

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Adaptive First-Order Methods for General Sparse Inverse Covariance Selection

SIAM journal on matrix analysis and applications, 2010-01, Vol.31 (4), p.2000-2016

Lu, Zhaosong

2010

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Robust portfolio selection based on a joint ellipsoidal uncertainty set

Optimization methods & software, 2011-02, Vol.26 (1), p.89-104

Lu, Zhaosong

2011

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Iterative reweighted minimization methods for lp regularized unconstrained nonlinear programming

Mathematical programming, 2014, Vol.147 (1-2), p.277-307

Lu, Zhaosong

2014

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Augmented Lagrangian method for tensor low-rank and sparsity models in multi-dimensional image recovery

Advances in computational mathematics, 2024-08, Vol.50 (4), Article 75

2024

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Iterative reweighted minimization methods for ... regularized unconstrained nonlinear programming

Mathematical programming, 2014-10, Vol.147 (1-2), p.277-307

Lu, Zhaosong

2014

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Dimension reduction and coefficient estimation in multivariate linear regression

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2007-06, Vol.69 (3), p.329-346

2007

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Iterative hard thresholding methods for l0 regularized convex cone programming

Mathematical programming, 2014, Vol.147 (1-2), p.125-154

Lu, Zhaosong

2014

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On the complexity analysis of randomized block-coordinate descent methods

Mathematical programming, 2015-08, Vol.152 (1-2), p.615-642

2015

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Iterative hard thresholding methods for ... regularized convex cone programming

Mathematical programming, 2014-10, Vol.147 (1-2), p.125-154

Lu, Zhaosong

2014

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ADAPTIVE FIRST-ORDER METHODS FOR GENERAL SPARSE INVERSE COVARIANCE SELECTION

SIAM journal on matrix analysis and applications, 2010, Vol.31 (4), p.2000-2016

Lu, Zhaosong

2010

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A computational study on robust portfolio selection based on a joint ellipsoidal uncertainty set

Mathematical programming, 2011, Vol.126 (1), p.193-201

Lu, Zhaosong

2011

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First-Order Penalty Methods for Bilevel Optimization

SIAM journal on optimization, 2024-06, Vol.34 (2), p.1937-1969

2024

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Primal-dual first-order methods with O(1/∈) iteration-complexity for cone programming

Mathematical programming, 2011, Vol.126 (1), p.1-29

2011

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Randomized Block Proximal Damped Newton Method for Composite Self-Concordant Minimization

SIAM journal on optimization, 2017-01, Vol.27 (3), p.1910-1942

Lu, Zhaosong

2017

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Accelerated First-Order Methods for Convex Optimization with Locally Lipschitz Continuous Gradient

SIAM journal on optimization, 2023-01, Vol.33 (3), p.2275-2310

2023

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A Newton-CG Based Barrier Method for Finding a Second-Order Stationary Point of Nonconvex Conic Optimization with Complexity Guarantees

SIAM journal on optimization, 2023-01, Vol.33 (2), p.1191-1222

2023

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Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming

SIAM journal on optimization, 2023-01, Vol.33 (2), p.1159-1190

2023

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Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression

Mathematical programming, 2012-02, Vol.131 (1-2), p.163-194

2012

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An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization

SIAM journal on optimization, 2015-01, Vol.25 (4), p.2244-2273

2015

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MINIMIZING CONDITION NUMBER VIA CONVEX PROGRAMMING

SIAM journal on matrix analysis and applications, 2011-10, Vol.32 (4), p.1193-1211

2011

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Einstellungen

Sparse Approximation via Penalty Decomposition Methods

Smooth Optimization Approach for Sparse Covariance Selection

Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming

An augmented Lagrangian approach for sparse principal component analysis

Sparse Recovery via Partial Regularization: Models, Theory, and Algorithms

Adaptive First-Order Methods for General Sparse Inverse Covariance Selection

Robust portfolio selection based on a joint ellipsoidal uncertainty set

Iterative reweighted minimization methods for lp regularized unconstrained nonlinear programming

Augmented Lagrangian method for tensor low-rank and sparsity models in multi-dimensional image recovery

Iterative reweighted minimization methods for ... regularized unconstrained nonlinear programming

Dimension reduction and coefficient estimation in multivariate linear regression

Iterative hard thresholding methods for l0 regularized convex cone programming

On the complexity analysis of randomized block-coordinate descent methods

Iterative hard thresholding methods for ... regularized convex cone programming

ADAPTIVE FIRST-ORDER METHODS FOR GENERAL SPARSE INVERSE COVARIANCE SELECTION

A computational study on robust portfolio selection based on a joint ellipsoidal uncertainty set

First-Order Penalty Methods for Bilevel Optimization

Primal-dual first-order methods with O(1/∈) iteration-complexity for cone programming

Randomized Block Proximal Damped Newton Method for Composite Self-Concordant Minimization

Accelerated First-Order Methods for Convex Optimization with Locally Lipschitz Continuous Gradient

A Newton-CG Based Barrier Method for Finding a Second-Order Stationary Point of Nonconvex Conic Optimization with Complexity Guarantees

Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming

Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression

An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization

MINIMIZING CONDITION NUMBER VIA CONVEX PROGRAMMING

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