An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
Ever-increasing memory footprint of applications and increasing mainstream popularity of shared memory parallel computing motivate us to explore memory compression potential in di...
GridXSLT is an implementation of the XSLT programming language designed for distributed web service orchestration. Based on the functional semantics of the language, it compiles p...
Peter M. Kelly, Paul D. Coddington, Andrew L. Wend...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...