In the classic multi-armed bandits problem, the goal is to have a policy for dynamically operating arms that each yield stochastic rewards with unknown means. The key metric of int...
On-line boosting is a recent advancement in the field of machine learning that has opened a new spectrum of possibilities in many diverse fields. With respect to a static strong...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
—Long time-series datasets are common in many domains, especially scientific domains. Applications in these fields often require comparing trajectories using similarity measure...
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...