Search Results - subject:"Sparse optimization"

On sparse reflexive generalized inverse

Fampa, Marcia Helena Costa; Lee, Jon - In: Operations research letters 46 (2018) 6, pp. 605-610

Persistent link: https://www.econbiz.de/10011957407

Generalized conjugate gradient methods for l1 regularized convex quadratic programming with finite convergence

Lu, Zhaosong; Chen, Xiaojun - In: Mathematics of operations research 43 (2018) 1, pp. 275-303

Persistent link: https://www.econbiz.de/10011818761

On the minimization over sparse symmetric sets : projections, optimality conditions, and algorithms

Beck, Amir; Hallak, Nadav - In: Mathematics of operations research 41 (2016) 1, pp. 196-223

Persistent link: https://www.econbiz.de/10011448357

Scalable rejection sampling for Bayesian hierarchical models

Braun, Michael; Damien, Paul - In: Marketing science 35 (2016) 3, pp. 427-444

Persistent link: https://www.econbiz.de/10011498936

DC approximation approaches for sparse optimization

Le Thi, H.A.; Pham Dinh, T.; Le, H.M.; Vo, X.T. - In: European Journal of Operational Research 244 (2015) 1, pp. 26-46

Sparse optimization refers to an optimization problem involving the zero-norm in objective or constraints. In this … paper, nonconvex approximation approaches for sparse optimization have been studied with a unifying point of view in DC …, to tackle the zero-norm and sparse optimization. As an application, we implemented our methods for the feature selection …

Persistent link: https://www.econbiz.de/10011209390

An adaptive accelerated proximal gradient method and its homotopy continuation for sparse optimization

Lin, Qihang; Xiao, Lin - In: Computational Optimization and Applications 60 (2015) 3, pp. 633-674

<Para ID="Par1">We consider optimization problems with an objective function that is the sum of two convex terms: one is smooth and given by a black-box oracle, and the other is general but with a simple, known structure. We first present an accelerated proximal gradient (APG) method for problems where the...</para>

Persistent link: https://www.econbiz.de/10011241264

DC approximation approaches for sparse optimization

Thi, H. A. Le; Dinh, T. Pham; Le, H. M.; Vo, X. T. - In: European journal of operational research : EJOR 244 (2015) 1, pp. 26-46

Persistent link: https://www.econbiz.de/10010531987

Sparse optimization in feature selection: application in neuroimaging

Kampa, K.; Mehta, S.; Chou, C.; Chaovalitwongse, W.; … - In: Journal of Global Optimization 59 (2014) 2, pp. 439-457

embedded feature selection framework that integrates sparse optimization for regularization (or sparse regularization) and …

Persistent link: https://www.econbiz.de/10010845820

Primal and dual alternating direction algorithms for ℓ <Subscript>1</Subscript>-ℓ <Subscript>1</Subscript>-norm minimization problems in compressive sensing

Xiao, Yunhai; Zhu, Hong; Wu, Soon-Yi - In: Computational Optimization and Applications 54 (2013) 2, pp. 441-459

In this paper, we propose, analyze and test primal and dual versions of the alternating direction algorithm for the sparse signal reconstruction from its major noise contained observation data. The algorithm minimizes a convex non-smooth function consisting of the sum of ℓ <Subscript>1</Subscript>-norm...</subscript>

Persistent link: https://www.econbiz.de/10010998348