We prove new lower bounds for learning intersections of halfspaces, one of the most important concept classes in computational learning theory. Our main result is that any statist...
Abstract. In this paper, we study lower bound techniques for branchand-bound algorithms for maximum parsimony, with a focus on gene order data. We give a simple O(n3 ) time dynamic...
Abraham Bachrach, Kevin Chen, Chris Harrelson, Rad...
This paper presents a framework that uses the outputs of model simplification to guide the construction of bounding volume hierarchies for use in, for example, collision detection...
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
We propose an algorithm which is an improved version of the Kabatiansky-Tavernier list decoding algorithm for the second order binary Reed-Muller code RM(2, m), of length n = 2m , ...