Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
With increasing process variation, binning has become an important technique to improve the values of fabricated chips, especially in high performance microprocessors where transpa...
High-level semi-Markov modelling paradigms such as semi-Markov stochastic Petri nets and process algebras are used to capture realistic performance models of computer and communic...
Marcel C. Guenther, Nicholas J. Dingle, Jeremy T. ...
nt, user-defined objects present an attractive abstraction for working with non-volatile program state. However, the slow speed of persistent storage (i.e., disk) has restricted ...
Joel Coburn, Adrian M. Caulfield, Ameen Akel, Laur...