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» Incremental Construction of Structured Hidden Markov Models
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BMCBI
2008
131views more  BMCBI 2008»
13 years 10 months ago
Major copy proportion analysis of tumor samples using SNP arrays
Background: Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers. Oligonucleotide SNP microarrays ha...
Cheng Li, Rameen Beroukhim, Barbara A. Weir, Wendy...
ECAI
1998
Springer
14 years 2 months ago
Optimal Scheduling of Dynamic Progressive Processing
Progressive processing allows a system to satisfy a set of requests under time pressure by limiting the amount of processing allocated to each task based on a predefined hierarchic...
Abdel-Illah Mouaddib, Shlomo Zilberstein
FLAIRS
2004
13 years 11 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
SIGMETRICS
2010
ACM
195views Hardware» more  SIGMETRICS 2010»
14 years 2 months ago
CWS: a model-driven scheduling policy for correlated workloads
We define CWS, a non-preemptive scheduling policy for workloads with correlated job sizes. CWS tackles the scheduling problem by inferring the expected sizes of upcoming jobs bas...
Giuliano Casale, Ningfang Mi, Evgenia Smirni
TASLP
2010
138views more  TASLP 2010»
13 years 5 months ago
Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...