We present some typical algorithms used for finding global minimum/maximum of a function defined on a compact finite dimensional set, discuss commonly observed procedures for assessing and comparing the algorithms’ performance and quote theoretical results on convergence of a broad class of stochastic algorithms
This paper presents some simple technical conditions that guarantee the convergence of a general cla...
Global optimization problems occur in many fields i ncluding mathematics, s tatistics, computer sci...
We develop numerical methods for solution of stochastic global optimization problems: min$[F(x)=Ef(x...
We present some typical algorithms used for finding global minimum/ maximum of a function defined on...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
The majority of stochastic optimization algorithms can be writ- ten in the general form $x_{t+1}= T...
This thesis presents the main results of two articles published by the authors in the field of stoc...
This paper deals with minimax problems in which the "inner" problem of maximization is not concave. ...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
Accelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, a...
We consider global optimization problems, where the feasible region X is a compact subset of Rd ...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
This paper presents some simple technical conditions that guarantee the convergence of a general cla...
A stochastic algorithm for bound-constrained global optimization is described. The method can be ap...
This paper presents some simple technical conditions that guarantee the convergence of a general cla...
Global optimization problems occur in many fields i ncluding mathematics, s tatistics, computer sci...
We develop numerical methods for solution of stochastic global optimization problems: min$[F(x)=Ef(x...
We present some typical algorithms used for finding global minimum/ maximum of a function defined on...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
The majority of stochastic optimization algorithms can be writ- ten in the general form $x_{t+1}= T...
This thesis presents the main results of two articles published by the authors in the field of stoc...
This paper deals with minimax problems in which the "inner" problem of maximization is not concave. ...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
Accelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, a...
We consider global optimization problems, where the feasible region X is a compact subset of Rd ...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
This paper presents some simple technical conditions that guarantee the convergence of a general cla...
A stochastic algorithm for bound-constrained global optimization is described. The method can be ap...
This paper presents some simple technical conditions that guarantee the convergence of a general cla...
Global optimization problems occur in many fields i ncluding mathematics, s tatistics, computer sci...
We develop numerical methods for solution of stochastic global optimization problems: min$[F(x)=Ef(x...
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