3 citations · 4 across the 3 of their papers we have counts for
4 papers
Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions
Roberto Battiti, Mauro Brunato
Bayesian Optimization (BO) for the minimization of expensive functions of continuous variables uses all the knowledge acquired from previous samples ( and $f({\b…
Reactive Sample Size for Heuristic Search in Simulation-based Optimization
Manuel Dalcastagné, Andrea Mariello, Roberto Battiti
In simulation-based optimization, the optimal setting of the input parameters of the objective function can be determined by heuristic optimization techniques. However, when simula…
A Telescopic Binary Learning Machine for Training Neural Networks
Mauro Brunato, Roberto Battiti
This paper proposes a new algorithm based on multi-scale stochastic local search with binary representation for training neural networks. In particular, we study the effects of nei…
Learning Modulo Theories for preference elicitation in hybrid domains
Paolo Campigotto, Roberto Battiti, Andrea Passerini
This paper introduces CLEO, a novel preference elicitation algorithm capable of recommending complex objects in hybrid domains, characterized by both discrete and continuous attrib…