Search Results - subject:"Gradient method"

On the connection between the conjugate gradient method and quasi-Newton methods on quadratic problems

Forsgren, Anders; Odland, Tove - In: Computational Optimization and Applications 60 (2015) 2, pp. 377-392

It is well known that the conjugate gradient method and a quasi-Newton method, using any well-defined update matrix … update matrix lies in the last two dimensions of the Krylov subspaces defined by the conjugate gradient method and that the … obtained in the conjugate gradient method is derived. In addition, we show that the update matrices from the one …

Persistent link: https://www.econbiz.de/10011241268

Notes on a 3-term Conjugacy Recurrence for the Iterative Solution of Symmetric Linear Systems

Fasano, Giovanni - Dipartimento di Matematica Applicata, Università Ca' … - 2008

We consider a 3-term recurrence, namely CG_2step, for the iterative solution of symmetric linear systems. The new algorithm generates conjugate directions and extends some standard theoretical properties of the Conjugate Gradient (CG) method [10]. We prove the finite convergence of CG_2step, and...

Persistent link: https://www.econbiz.de/10005566307

Incremental accelerated gradient methods for SVM classification : study of the constrained approach

Couellan, Nicolas; Jan, Sophie - In: Computational Management Science : CMS 11 (2014) 4, pp. 419-444

Persistent link: https://www.econbiz.de/10010437148

A derivative-free algorithm for linearly constrained optimization problems

Gumma, E.; Hashim, M.; Ali, M. - In: Computational Optimization and Applications 57 (2014) 3, pp. 599-621

second derivative matrix of the model. The model is then minimized by a trust-region subproblem using the conjugate gradient … method for a new iterate. At times the new iterate is found from a model iteration, designed to improve the geometry of the …

Persistent link: https://www.econbiz.de/10010998298

Sparse trace norm regularization

Chen, Jianhui; Ye, Jieping - In: Computational Statistics 29 (2014) 3, pp. 623-639

We study the problem of estimating multiple predictive functions from a dictionary of basis functions in the nonparametric regression setting. Our estimation scheme assumes that each predictive function can be estimated in the form of a linear combination of the basis functions. By assuming that...

Persistent link: https://www.econbiz.de/10010998470

Incremental accelerated gradient methods for SVM classification: study of the constrained approach

Couellan, Nicolas; Jan, Sophie - In: Computational Management Science 11 (2014) 4, pp. 419-444

We investigate constrained first order techniques for training support vector machines (SVM) for online classification tasks. The methods exploit the structure of the SVM training problem and combine ideas of incremental gradient technique, gradient acceleration and successive simple...

Persistent link: https://www.econbiz.de/10010949671

On proximal gradient method for the convex problems regularized with the group reproducing kernel norm

Zhang, Haibin; Wei, Juan; Li, Meixia; Zhou, Jie; Chao, … - In: Journal of Global Optimization 58 (2014) 1, pp. 169-188

approach to solve such problems is by the proximal gradient method. In this paper we derive and study theoretically the …

Persistent link: https://www.econbiz.de/10010845793

Path-following gradient-based decomposition algorithms for separable convex optimization

Dinh, Quoc Tran; Necoara, Ion; Diehl, Moritz - In: Journal of Global Optimization 59 (2014) 1, pp. 59-80

dual variables using a path-following gradient method and allows one to solve the subproblems in parallel. Moreover …

Persistent link: https://www.econbiz.de/10010845803

Efficient algorithms for robust and stable principal component pursuit problems

Aybat, Necdet; Goldfarb, Donald; Ma, Shiqian - In: Computational Optimization and Applications 58 (2014) 1, pp. 1-29

The problem of recovering a low-rank matrix from a set of observations corrupted with gross sparse error is known as the robust principal component analysis (RPCA) and has many applications in computer vision, image processing and web data ranking. It has been shown that under certain...

Persistent link: https://www.econbiz.de/10010847445

A modified scaled memoryless BFGS preconditioned conjugate gradient method for unconstrained optimization

Babaie-Kafaki, Saman - In: 4OR : a quarterly journal of operations research 11 (2013) 4, pp. 361-374

Persistent link: https://www.econbiz.de/10010227999