We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
A compressed full-text self-index for a text T , of size u, is a data structure used to search for patterns P, of size m, in T , that requires reduced space, i.e. space that depend...
We address the vexing issue of deletions in balanced trees. Rebalancing after a deletion is generally more complicated than rebalancing after an insertion. Textbooks neglect delet...
Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...