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On variance reduction for stochastic smooth convex optimization with multiplicative noise
(Springer Verlag, 2019)
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society. We propose dynamic sampled stochastic approximation (SA) methods for stochastic optimization with a heavy-tailed distribution ...
Hessian Riemannian gradient flows in convex programming
(SIAM PUBLICATIONS, 2004)
In view of solving theoretically constrained minimization problems, we investigate the properties of the gradient flows with respect to Hessian Riemannian metrics induced by Legendre functions. The first result characterizes ...
(A, B)-invariant polyhedral sets of linear discrete-time systems
(1999)
The problem of confining the trajectory of a linear discrete-time system in a given polyhedral domain is addressed through the concept of (A, B)-invariance. First, an explicit characterization of (A, B)-invariance of convex ...
Lagrangian penalization scheme with parallel forward-backward splitting
(Springer, 2018-05)
We propose a new iterative algorithm for the numerical approximation of the solutions to convex optimization problems and constrained variational inequalities, especially when the functions and operators involved have a ...
Characterizing the Convexity of Joint-Range for a Pair of Inhomogeneous Quadratic Functions and Strong Duality
(2016)
We establish various extensions of the convexity Dines theorem for a (joint-range) pair of inhomogeneous quadratic functions. If convexity fails we describe those rays for which the sum of the joint-range and the ray is ...
Efficient Day-Ahead Dispatch of Photovoltaic Sources in Monopolar DC Networks via an Iterative Convex Approximation
(Cartagena de Indias, 2023)
The objective of this research is to propose an efficient energy management system for photovoltaic (PV) generation units connected to monopolar DC distribution networks via convex optimization while considering a day-ahead ...
A convex chance-constrained model for reactive power planning
(2015-10-01)
This paper presents a new approach for long-term reactive power investment planning and operation using a multiperiod mixed-integer stochastic convex model, where load uncertainty is also included. The risk of not meeting ...