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...
Large information spaces are often difficult to access efficiently and intuitively. We are exploring Pad++, a graphical interface system based on zooming, as an alternative to tra...
Abstract. This paper considers the general problem of function estimation with a modular approach of neural computing. We propose to use functionally independent subnetworks to lea...
Abstract. We consider the communication complexity of the binary inner product function in a variation of the two-party scenario where the parties have an a priori supply of partic...
Richard Cleve, Wim van Dam, Michael Nielsen, Alain...
We study the link between the complexity of a polynomial and that of its coefficient functions. Valiant’s theory is a good setting for this, and we start by generalizing one of V...