We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of...
Edmund K. Burke, Jakub Marecek, Andrew J. Parkes, ...
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
Abstract. We describe a simple CSP formalism for handling multi-attribute preference problems with hard constraints, one that combines hard constraints and preferences so the two a...
Eugene C. Freuder, Robert Heffernan, Richard J. Wa...
— In this paper, we will study the problem of projected clustering of uncertain data streams. The use of uncertainty is especially important in the high dimensional scenario, bec...