Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Abstract. In this work, we address the problem of transient and steadystate analysis of a stochastic Petri net which includes non Markovian distributions with a finite support but ...
We present a possible world semantics for a call-by-value higherorder programming language with impredicative polymorphism, general references, and recursive types. The model is o...
Abstract. The paper presents a deductive framework for proving program equivalence and its application to automatic verification of transformations performed by optimizing compiler...
—We investigate a new class of codes for the optimal covering of vertices in an undirected graph Gsuch that any vertex in G can be uniquely identified by examining the vertices ...
Mark G. Karpovsky, Krishnendu Chakrabarty, Lev B. ...