Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usu...
Proving termination of sequential programs is an important problem, both for establishing the total correctness of systems and as a component of proving more general termination an...
William R. Harris, Akash Lal, Aditya V. Nori, Srir...
Recently, graphics hardware architectures have begun to emphasize versatility, offering rich new ways to programmatically reconfigure the graphics pipeline. In this paper, we exp...
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...