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» Dynamic power management using machine learning
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BMCBI
2010
153views more  BMCBI 2010»
15 years 3 months ago
MimoSA: a system for minimotif annotation
Background: Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they a...
Jay Vyas, Ronald J. Nowling, Thomas Meusburger, Da...

Lab
652views
17 years 2 months ago
Electronic Enterprises Laboratory
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...
144
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ASPLOS
2012
ACM
13 years 11 months ago
Chameleon: operating system support for dynamic processors
The rise of multi-core processors has shifted performance efforts towards parallel programs. However, single-threaded code, whether from legacy programs or ones difficult to para...
Sankaralingam Panneerselvam, Michael M. Swift
ECML
2001
Springer
15 years 8 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
143
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COR
2008
142views more  COR 2008»
15 years 3 months ago
Application of reinforcement learning to the game of Othello
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
Nees Jan van Eck, Michiel C. van Wezel