We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
Nonnegative Matrix Factorization (NMF) is a powerful decomposition tool which has been used in several content representation applications recently. However, there are some diffic...
This paper proposes a new concept in hierarchical representations that exploits features of different granularity and specificity coming from all layers of the hierarchy. The conc...
Information Retrieval (IR) systems are built with different goals in mind. Some IR systems target high precision that is to have more relevant documents on the first page of their...
It has been of great interest to find sparse and/or nonnegative representations in computer vision literature. In this paper we propose a novel method to such a purpose and refer...