نتایج جستجو برای: mollifier subgradient

تعداد نتایج: 1200  

2007
T. Sun P. B. Luh

When applied to large-scale separable optimization problems, the recently developed surrogate subgradient method for Lagrangian relaxation (Zhao et al.: J. Optim. Theory Appl. 100, 699–712, 1999) does not need to solve optimally all the subproblems to update the multipliers, as the traditional subgradient method requires. Based on it, the penalty surrogate subgradient algorithm was further deve...

2012
W. HARE C. SAGASTIZÁBAL M. SOLODOV

We consider the problem of computing a critical point of a nonconvex locally Lipschitz function over a convex compact constraint set given an inexact oracle that provides an approximate function value and an approximate subgradient. We assume that the errors in function and subgradient evaluations are merely bounded, and in particular need not vanish in the limit. After some discussion on how t...

Journal: :Math. Program. 2006
Georg Ch. Pflug

Measures of risk appear in two categories: Risk capital measures serve to determine the necessary amount of risk capital in order to avoid ruin if the outcomes of an economic activity are uncertain and their negative values may be interpreted as acceptability measures (safety measures). Pure risk measures (risk deviation measures) are natural generalizations of the standard deviation. While pur...

Journal: :Telecommunication Systems 2000
Deep Medhi David Tipper

In this paper, we consider solution approaches to a multihour combined capacity design and routing problem which arises in the design of dynamically reconfigurable broadband communication networks that uses the virtual path concept. We present a comparative evaluation of four approaches, namely: a genetic algorithm, a Lagrangian relaxation based subgradient optimization method, a generalized pr...

Journal: :J. Optimization Theory and Applications 2014
Yair Censor Ran Davidi Gabor T. Herman Reinhard W. Schulte Luba Tetruashvili

The projected subgradient method for constrained minimization repeatedly interlaces subgradient steps for the objective function with projections onto the feasible region, which is the intersection of closed and convex constraints sets, to regain feasibility. The latter poses a computational difficulty and, therefore, the projected subgradient method is applicable only when the feasible region ...

Journal: :Signal Processing 2006
Alper T. Erdogan

SubGradient based Blind Algorithm (SGBA) has recently been introduced [A.T. Erdogan, C. Kizilkale, Fast and low complexity blind equalization via subgradient projections, IEEE Trans. Signal Process. 53 (2005) 2513–2524; C. Kizilkale, A.T. Erdogan, A fast blind equalization method based on subgradient projections, Proceedings of IEEE ICASSP 2004, Montreal, Canada, vol. 4, pp. 873–876.] as a conv...

Journal: :Journal of Machine Learning Research 2010
John C. Duchi Elad Hazan Yoram Singer

We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradientbased learning. Metaphorically, the adaptation allows us to find needles in haystacks in the form of very predictive but rarely seen features. Our paradigm stems from recent advances in stochastic optimization and on...

2008
E. Mijangos

The minimization of nonlinearly constrained network flow problems can be performed by using approximate subgradient methods. The idea is to solve this kind of problem by means of primal-dual methods, given that the minimization of nonlinear network flow problems can be efficiently done by exploiting the network structure. In this work it is proposed to solve the dual problem by using 2subgradie...

1999
D Medhi D Tipper

In this paper, we consider solution approaches to a multi-hour combined capacity design and routing problem which arises in the design of dynamically reconngurable broadband communication networks that uses the virtual path concept. We present a comparative evaluation of four approaches, namely: a genetic algorithm; a Lagrangean relaxation based subgradient optimization method; a generalized pr...

Journal: :IEEE transactions on cybernetics 2017
Youcheng Lou Lean Yu Shouyang Wang

In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show t...

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