We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
The Designers’ Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as RollsRoyce, by makin...
Suraj Ajit, Derek H. Sleeman, David W. Fowler, Dav...
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...