This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
We present a learning algorithm for nominal data. It builds a classifier by adding iteratively a simple patch function that modifies the current classifier. Its main advantage lies...
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
The Valued Constraint Satisfaction Problem (VCSP) is a generic optimization problem defined by a network of local cost functions defined over discrete variables. It has applicatio...
Martin C. Cooper, Simon de Givry, M. Sanchez, Thom...