We provide efficient algorithms for finding approximate BayesNash equilibria (BNE) in graphical, specifically tree, games of incomplete information. In such games an agent’s p...
Satinder P. Singh, Vishal Soni, Michael P. Wellman
MAX-SAT, the optimisation variant of the satisfiability problem in propositional logic, is an important and widely studied combinatorial optimisation problem with applications in ...
Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
In this study, the generalized parametric spectral subtraction estimator is employed in the context of a ROVER speech enhancement framework to develop a robust phoneme class selec...
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...