The group mutual exclusion problem extends the traditional mutual exclusion problem by associating a type with each critical section. In this problem, processes requesting critica...
In this paper, we study the problem of finding optimal mappings for several independent but concurrent workflow applications, in order to optimize performance-related criteria tog...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Providing up-to-date input to users’ applications is an important data management problem for a distributed computing environment, where each data storage location and intermedi...
Mitchell D. Theys, Noah Beck, Howard Jay Siegel, M...
We present a combinatorial framework for the study of a natural class of distributed optimization problems that involve decisionmaking by a collection of n distributed agents in th...