In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
This paper presents a new technique, called Symbolic Program Decomposition (or SPD), for symbolic execution of multiple paths that is more scalable than existing techniques, which...
In 2006, John Mellor-Crummey and Michael Scott received the Dijkstra Prize in Distributed Computing. This prize was for their 1991 paper on algorithms for scalable synchronization ...
In this paper, we present parallel multilevel algorithms for the hypergraph partitioning problem. In particular, we describe schemes for parallel coarsening, parallel greedy k-way...