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» Tackling Large State Spaces in Performance Modelling
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MASCOTS
2010
13 years 6 months ago
Black-Box Performance Modeling for Solid-State Drives
—Flash-based Solid-State Drives (SSDs) have become a promising alternative to magnetic Hard Disk Drives (HDDs) thanks to the large improvements in performance, power consumption,...
Shan Li, H. Howie Huang
IROS
2007
IEEE
148views Robotics» more  IROS 2007»
14 years 1 months ago
Tractable probabilistic models for intention recognition based on expert knowledge
— Intention recognition is an important topic in human-robot cooperation that can be tackled using probabilistic model-based methods. A popular instance of such methods are Bayes...
Oliver C. Schrempf, David Albrecht, Uwe D. Hanebec...
ICML
2009
IEEE
14 years 8 months ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Thierry Artières, Trinh Minh Tri Do
ICSE
2007
IEEE-ACM
14 years 7 months ago
Parallel Randomized State-Space Search
Model checkers search the space of possible program behaviors to detect errors and to demonstrate their absence. Despite major advances in reduction and optimization techniques, s...
Matthew B. Dwyer, Sebastian G. Elbaum, Suzette Per...
VOSS
2004
Springer
152views Mathematics» more  VOSS 2004»
14 years 28 days ago
Symbolic Representations and Analysis of Large Probabilistic Systems
Abstract. This paper describes symbolic techniques for the construction, representation and analysis of large, probabilistic systems. Symbolic approaches derive their efficiency by...
Andrew S. Miner, David Parker