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» Using Goal-Models to Analyze Variability
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CORR
2011
Springer
150views Education» more  CORR 2011»
13 years 2 months ago
Total variation regularization for fMRI-based prediction of behaviour
—While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI ...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
ICS
2005
Tsinghua U.
14 years 1 months ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
VITCOMIC: visualization tool for taxonomic compositions of microbial communities based on 16S rRNA gene sequences
Background: Understanding the community structure of microbes is typically accomplished by sequencing 16S ribosomal RNA (16S rRNA) genes. These community data can be represented b...
Hiroshi Mori, Fumito Maruyama, Ken Kurokawa
DSS
2008
103views more  DSS 2008»
13 years 7 months ago
Explaining clinical decisions by extracting regularity patterns
When solving clinical decision-making problems with modern graphical decision-theoretic models such as influence diagrams, we obtain decision tables with optimal decision alternat...
Concha Bielza, Juan A. Fernández del Pozo, ...
ASPLOS
2008
ACM
13 years 9 months ago
Exploiting access semantics and program behavior to reduce snoop power in chip multiprocessors
Integrating more processor cores on-die has become the unanimous trend in the microprocessor industry. Most of the current research thrusts using chip multiprocessors (CMPs) as th...
Chinnakrishnan S. Ballapuram, Ahmad Sharif, Hsien-...