Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
The SISSI program implements a novel approach for the estimation of the optimal sample size in experimental data collection. It provides avisual evaluation system of sample size d...
Roberto Confalonieri, Marco Acutis, Gianni Bellocc...
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
LABATCH.2 is a collection of computer programs available in C, FORTRAN, and SIMSCRIPT II.5 by anonymous ftp, at http://www.or.unc.edu/gfish/labatch.2.html. It performs statistical...
Abstract. In this paper we present a novel analysis of a random sampling approach for three clustering problems in metric spaces: k-median, min-sum kclustering, and balanced k-medi...