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ICCAD
1994
IEEE
90views Hardware» more  ICCAD 1994»
13 years 8 months ago
Algorithm selection: a quantitative computation-intensive optimization approach
Given a set of specifications for a targeted application, algorithm selection refers to choosing the most suitable algorithm for a given goal, among several functionally equivalen...
Miodrag Potkonjak, Jan M. Rabaey
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 5 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
BMCBI
2010
106views more  BMCBI 2010»
13 years 4 months ago
Selection of optimal reference genes for normalization in quantitative RT-PCR
Background: Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introdu...
Inna Chervoneva, Yanyan Li, Stephanie Schulz, Sean...
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
13 years 2 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
EVOW
1999
Springer
13 years 9 months ago
Test Pattern Generation Under Low Power Constraints
A technique is proposed to reduce the peak power consumption of sequential circuits during test pattern application. High-speed computation intensive VLSI systems, as telecommunica...
Fulvio Corno, Maurizio Rebaudengo, Matteo Sonza Re...