We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Data-layout optimizations rearrange fields within objects, objects within objects, and objects within the heap, with the goal of increasing spatial locality. While the importance ...
Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring u...
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
Scientific data in the life sciences is distributed over various independent multi-format databases and is constantly expanding. We discuss a scenario where a life science research...