Results 21 to 30 of about 326,649 (319)
Predictive online convex optimization [PDF]
We incorporate future information in the form of the estimated value of future gradients in online convex optimization. This is motivated by demand response in power systems, where forecasts about the current round, e.g., the weather or the loads' behavior, can be used to improve on predictions made with only past observations.
Joshua A. Taylor +2 more
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On Convex optimization without convex representation [PDF]
7 pages; 1 ...
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Characterizations of the Solution Sets of Generalized Convex Fuzzy Optimization Problem
This paper provides some new characterizations of the solution sets for non-differentiable generalized convex fuzzy optimization problem. Firstly, we introduce some new generalized convex fuzzy functions and discuss the relationships among them. Secondly,
Chen Wang, Zhou Zhiang
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A Note on Optimality Conditions for DC Programs Involving Composite Functions
By using the formula of the ε-subdifferential for the sum of a convex function with a composition of convex functions, some necessary and sufficient optimality conditions for a DC programming problem involving a composite function are obtained.
Xiang-Kai Sun, Hong-Yong Fu
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In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization.
Q. L. Dong +4 more
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Multimodularity, Convexity, and Optimization Properties [PDF]
In this paper we investigate the properties of multimodular functions. In doing so we give elementary proofs for properties already established by Hajek and we generalize some of his results. In particular, we extend the relation between convexity and multimodularity to some convex subsets of ℤm. We also obtain general optimization results for average
Altman, Eitan +2 more
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Manifold Optimization Over the Set of Doubly Stochastic Matrices: A Second-Order Geometry [PDF]
Convex optimization is a well-established research area with applications in almost all fields. Over the decades, multiple approaches have been proposed to solve convex programs.
Douik, Ahmed, Hassibi, Babak
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ROBOTIC MOTION PLANNING USING CONVEX OPTIMIZATION METHODS
Collision avoidance techniques tend to derive the robot away of the obstacles in minimal total travel distance. Most of the collision avoidance algorithms have trouble get stuck in a local minimum.
Thaker Nayl
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Convex Optimization on Banach Spaces [PDF]
Greedy algorithms which use only function evaluations are applied to convex optimization in a general Banach space $X$. Along with algorithms that use exact evaluations, algorithms with approximate evaluations are treated. A priori upper bounds for the convergence rate of the proposed algorithms are given.
Ronald A. DeVore, Vladimir Temlyakov
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Some Inequalities of Generalized p-Convex Functions concerning Raina’s Fractional Integral Operators
Convex functions play an important role in pure and applied mathematics specially in optimization theory. In this paper, we will deal with well-known class of convex functions named as generalized p-convex functions.
Changyue Chen +2 more
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