The purpose of this paper is to analyse the maxima properties (value and position) of some data structures. Our theorems concern the distribution of the random variables. Previously known results usually dealt with the mean and sometimes the variance of these random variables. Many of our results rely on diffusion techniques. That is a very powerful tool, which has already been used with some success in the analysis of algorithms.SCOPUS: cp.kinfo:eu-repo/semantics/publishe
SUMMARY Explicit solution of the problem of maximization of information divergence from the family o...
The maximum entropy principle introduced by Jaynes proposes that a data distribution should maximize...
Abstract: This paper deals with the limiting distribution of the maximum, under linear normalization...
The purpose of this paper is to analyze the maxima properties (value and position) of some data stru...
Projet EURECAThe purpose of this paper is to analyze the maxima properties (value and position) of s...
AbstractWe present a new approach for an average-case analysis of algorithms and data structures tha...
Estimation of Distribution Algorithms EDA have been proposed as an extension of genetic algorithms. ...
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds...
This chapter serves as an introduction to estimation of distribution algorithms (EDAs). Estimation o...
Markov networks and other probabilistic graphical modes have recently received an upsurge in attenti...
In the field of optimization using probabilistic models of the search space, this thesis identifies ...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
This paper investigates the statistical properties of maximum likelihood estimation index of the Par...
Abstract—Metaheuristics assume some kind of coherence between decision and objective spaces. Estimat...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
SUMMARY Explicit solution of the problem of maximization of information divergence from the family o...
The maximum entropy principle introduced by Jaynes proposes that a data distribution should maximize...
Abstract: This paper deals with the limiting distribution of the maximum, under linear normalization...
The purpose of this paper is to analyze the maxima properties (value and position) of some data stru...
Projet EURECAThe purpose of this paper is to analyze the maxima properties (value and position) of s...
AbstractWe present a new approach for an average-case analysis of algorithms and data structures tha...
Estimation of Distribution Algorithms EDA have been proposed as an extension of genetic algorithms. ...
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds...
This chapter serves as an introduction to estimation of distribution algorithms (EDAs). Estimation o...
Markov networks and other probabilistic graphical modes have recently received an upsurge in attenti...
In the field of optimization using probabilistic models of the search space, this thesis identifies ...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
This paper investigates the statistical properties of maximum likelihood estimation index of the Par...
Abstract—Metaheuristics assume some kind of coherence between decision and objective spaces. Estimat...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
SUMMARY Explicit solution of the problem of maximization of information divergence from the family o...
The maximum entropy principle introduced by Jaynes proposes that a data distribution should maximize...
Abstract: This paper deals with the limiting distribution of the maximum, under linear normalization...