Supervised learning of a parts-based model can be for-
mulated as an optimization problem with a large (exponen-
tial in the number of parts) set of constraints. We show how
thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
In this paper we study the expressive power of query languages for nested bags. We de ne the ambient bag language by generalizing the constructs of the relational language of Brea...
Symmetries are not only fascinating, but they can also be exploited when designing numerical algorithms and data structures for scientific engineering problems in symmetrical doma...