This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
We study the subsequence packing problem: given a string T and a collection of strings {Si}, find disjoint subsequences {Ti} of T with maximum total length such that each Ti is a ...
Greedy algorithms are simple, but their relative power is not well understood. The priority framework [5] captures a key notion of “greediness” in the sense that it processes (...
The unsplittable flow problem is one of the most extensively studied optimization problems in the field of networking. An instance of it consists of an edge capacitated graph and ...
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...