In one-class classification we seek a rule to find a coherent subset of instances similar to a few positive examples in a large pool of instances. The problem can be formulated an...
Koby Crammer, Partha Pratim Talukdar, Fernando Per...
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
We describe a formal framework for diagnosis and repair problems that shares elements of the well known partially observable MDP and cost-sensitive classification models. Our cost...
Michael L. Littman, Nishkam Ravi, Eitan Fenson, Ri...
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...