Abstract. In the constraint satisfaction problem (CSP), the aim is to find an assignment of values to a set of variables subject to specified constraints. In the minimum cost hom...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
"Cluster analysis is an important technique in the rapidly growing field known as exploratory data analysis and is being applied in a variety of engineering and scientific dis...
Abstract. We present a detailed investigation of the scalability characteristics of the SPEC OpenMP benchmarks on large-scale shared memory multiprocessor machines. Our study is ba...
Abstract. Bulk Synchronous Parallel ML or BSML is a functional dataparallel language for programming bulk synchronous parallel (BSP) algorithms. The execution time can be estimated...