Abstract. We give a method for modular generation of ground interpolants in modern SMT solvers supporting multiple theories. Our method uses a novel algorithm to modify the proof t...
We present a combination method for generating interpolants for a class of first-order theories. Using interpolant-generation procedures for individual theories as black-boxes, our...
We study parallel algorithms for computing the minimum spanning tree of a weighted undirected graph G with n vertices and m edges. We consider an input graph G with m=n p, where p...
We show how a general quantitative theory of neural computation can be used to explain two recent experimental findings in neuroscience. The first of these findings is that in hum...
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...