Descent Methods
Finite Step Relaxed Hybrid Steepest Descent Methods for Variational Inequalities
... class of hybrid steepest-descent methods for solving VIF, C has been introduced and studied recently by many authors see, e.g., 3, 4. Zeng and Yao 2 have established the method of two-step relaxed hybrid ...
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Iteration Complexity of Feasible Descent Methods for Convex Optimization
... In many machine learning problems such as the dual form of SVM, the objective function to be minimized is convex but not strongly convex. This fact causes difficulties in obtaining the complexity of some commonly used ...
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An Application of Hybrid Steepest Descent Methods for Equilibrium Problems and Strict Pseudocontractions in Hilbert Spaces
... steepest descent methods for finding a common element of the set of solutions of an equilibrium problem and the set of fixed points of a strict pseudocontraction mapping in the setting of real Hilbert ...
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Descent methods for convex optimization problems in Banach spaces
... In this paper, motivated by the above approach, we intend to present a rather general class of implementable algorithms for solving the convex optimization problem (1.2) in a reflexive Banach space. These algorithms have ...
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Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption
... order methods belong to the class of FDMs, (where inexact meth- ods are methods that incorporate some kind of inexact information, for example, via inexact gradients, or via inexact ...coordinate ...
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Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
... Besides IS methods, numerous optimization methods have been applied to train Maxent. For example, Liu and Nocedal (1989), Bottou (2004), Daum´e (2004), Keerthi et al. (2005), McDonald and Pereira (2006), ...
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Strong convergence of relaxed hybrid steepest-descent methods for triple hierarchical constrained optimization
... The rest of the article is organized as follows. After some preliminaries in Section 2, we introduce two relaxed hybrid steepest-descent algorithms for solving Problems I and II in Section 3, respectively. Strong ...
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A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification
... optimization methods for least-square ...coordinate descent methods, although they allowed a block of variables at each ...coordinate descent method, but used the gradient information for ...
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Hybrid Steepest Descent Method with Variable Parameters for General Variational Inequalities
... [11] I. Yamada, “The hybrid steepest-descent method for variational inequality problems over the intersection of the fixed point sets of nonexpansive mappings,” in Inherently Parallel Algorithms in Feasibility and ...
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Optimal Control of Microgrid Networks Using Gradient Descent and Differential Evolution Methods
... gradient methods are learnt from ...These methods to the best of our knowledge, it has never been applied to control Microgrid ...Gradient descent methods ...
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On the convergence speed of artificial neural networks in the solving of linear systems
... Variable metric algorithms also called quasi- Newton or matrix iteration algorithms, have proved to be the most effective class of general- purpose methods for solving unconstrained min- imization problems. Their ...
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A New Nonlinear Conjugate Gradient Method Based on the Scaled Matrix
... In this paper, we have proposed new a nonlinear CG- algorithms based on the Scaled Matrix defined by (17) under some assumptions. The new algorithm has been shown to be globally convergent and satisfies the ...
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A THEORETICAL SURVEY OF GRADIENT BASED ALGORITHMS FOR MULTIVARIABLE OPTIMIZATION
... In the DFP method, the modification of the matrix, using equation (8) preserves the symmetry and the positive-definiteness of the matrix. This property makes the DFP method attractive. Recall that in order to achieve a ...
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Effectiveness of Breeding Methods for Production of Superior Genotypes and Maintenance of Genetic Variance in Faba Bean (Vicia faba, L.)
... selection methods and three intervarietal crosses of ...seed descent, pedigree selection and bulk methods to conduct effective selection for the improvement of yield and its ...selection ...
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An Improved Gauss Newtons Method based Back propagation Algorithm for Fast Convergence
... steepest descent back-propagation (SDBP) is used in several applications despite its asymptotic slow convergence rate ...steepest descent algorithm encourages many ides to be developed for faster ...
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Prevention and treatment of high altitude cerebral edema (HACE)
... prevention. Methods of treatments of acute mountain sickness are highly effective in high altitude cerebral edema ...of descent, administration of acetazolamide and dexamethasone, oxygen therapy as well as ...
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Projection based algorithms for variational inequalities
... This chapter proposes two algorithms for solution of variational inequalities. Both of them be- long to the broad category of projection based algorithms. The goal in developing these algorithms is twofold. First, the ...
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Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator
... gradient descent (SGD) is a scalable algorithm to compute parameter estimates and has gained increasing popularity due to its numerical convenience and memory ...
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On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
... RBCGD methods, we also consider a variant of the CBCGD method named the permuted BCGD (PBCGD) method, which randomly permutes all indices for the p blocks in each ...PBCGD methods are inherently stochastic, ...
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Three modified Polak Ribière Polyak conjugate gradient methods with sufficient descent property
... gradient methods, which are some improvements of recently proposed PRP conjugate gradient ...proposed methods are established under the Wolfe line ...proposed methods have been shown by some ...
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