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WSC
1997
15 years 7 months ago
Seven Habits of Highly Successful Input Modelers
Discrete-event simulation models typically have stochastic components that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a c...
Lawrence Leemis
ICSE
2012
IEEE-ACM
13 years 8 months ago
Engineering and verifying requirements for programmable self-assembling nanomachines
—We propose an extension of van Lamsweerde’s goal-oriented requirements engineering to the domain of programmable DNA nanotechnology. This is a domain in which individual devic...
Robyn R. Lutz, Jack H. Lutz, James I. Lathrop, Tit...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 6 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
15 years 12 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
BMCBI
2005
89views more  BMCBI 2005»
15 years 6 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg