We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
New biological experimental techniques are continuing to generate large amounts of data using DNA, RNA, human genome and protein sequences. The quantity and quality of data from t...
We suggest a new technique to reduce energy consumption in the processor datapath without sacrificing performance by exploiting operand value locality at run time. Data locality is...
Instruction reuse is a microarchitectural technique that improves the execution time of a program by removing redundant computations at run-time. Although this is the job of an op...
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...