We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
This paper discusses how a robot can develop its state vector according to the complexity of the interactions with its environment. A method for controlling the complexity is prop...
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
In this paper, we describe two mission critical applications currently deployed by Telecom Italia in the Operations Support System domains. The first one called "Network Neut...