Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...
The time-bounded reachability problem for continuoustime Markov chains (CTMCs) amounts to determine the probability to reach a (set of) goal state(s) within a given time span, suc...
We present the design and implementation of APL Intrinsic Functions for a Finite State Machine (also known as a Finite State Automaton) which recognizes regular languages, and a P...
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...