We show how to compute an LU factorization of a matrix when the factors of a leading principle submatrix are already known. The approach incorporates pivoting akin to partial pivo...
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Small-bias, or -biased, spaces have found many applications in complexity theory, coding theory, and derandomization. We generalize the notion of small-bias spaces to the setting ...
We present a unification-based, context-sensitive escape and effect analysis that infers lightweight method summaries describing heap effects. The analysis is parameterized on two...
Abstract. We present an algorithmic framework for integrating solution methods that is based on search, inference, and relaxation and their interactions. We show that the following...