A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Distributed real-time and embedded (DRE) systems have stringent constraints on timeliness and other properties whose assurance is crucial to correct system behavior. Formal tools ...
Venkita Subramonian, Christopher D. Gill, Cé...
As feature sizes shrink, transient failures of on-chip network links become a critical problem. At the same time, many applications require guarantees on both message arrival prob...
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Inspired by AND/OR search spaces for graphical models recently introduced, we propose to augment Multi-Valued Decision Diagrams (MDD) with AND nodes, in order to capture function ...
Robert Mateescu, Rina Dechter, Radu Marinescu 0002