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» On Using Monte Carlo Methods for Scheduling
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MMB
2010
Springer
194views Communications» more  MMB 2010»
14 years 9 days ago
Searching for Tight Performance Bounds in Feed-Forward Networks
Abstract. Computing tight performance bounds in feed-forward networks under general assumptions about arrival and server models has turned out to be a challenging problem. Recently...
Andreas Kiefer, Nicos Gollan, Jens B. Schmitt
JCB
2008
159views more  JCB 2008»
13 years 7 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther
BIBE
2010
IEEE
144views Bioinformatics» more  BIBE 2010»
13 years 8 months ago
Knowledge-Guided Docking of Flexible Ligands to SH2 Domain Proteins
Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling and regulation. In this work, we applied a three-stage knowledg...
Haiyun Lu, Shamima Banu Bte Sm Rashid, Hao Li, Wee...
IPMI
2003
Springer
14 years 22 days ago
Ideal-Observer Performance under Signal and Background Uncertainty
We use the performance of the Bayesian ideal observer as a figure of merit for hardware optimization because this observer makes optimal use of signal-detection information. Due t...
Subok Park, Matthew A. Kupinski, Eric Clarkson, Ha...
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 10 days ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel