This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
This paper addresses the task of trajectory cost prediction, a new learning task for trajectories. The goal of this task is to predict the cost for an arbitrary (possibly unknown)...
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
Eric van den Berg, Praveen Gopalakrishnan, Byungsu...