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» On the possibility of faster SAT algorithms
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87
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FOCS
2008
IEEE
14 years 11 months ago
Set Covering with our Eyes Closed
Given a universe U of n elements and a weighted collection S of m subsets of U, the universal set cover problem is to a-priori map each element u ∈ U to a set S(u) ∈ S contain...
Fabrizio Grandoni, Anupam Gupta, Stefano Leonardi,...
99
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BMCBI
2008
211views more  BMCBI 2008»
14 years 10 months ago
CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment
Background: Searching for similarities in protein and DNA databases has become a routine procedure in Molecular Biology. The Smith-Waterman algorithm has been available for more t...
Svetlin Manavski, Giorgio Valle
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
15 years 7 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
ICAC
2006
IEEE
15 years 4 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...
GECCO
2005
Springer
111views Optimization» more  GECCO 2005»
15 years 3 months ago
XCS with eligibility traces
The development of the XCS Learning Classifier System has produced a robust and stable implementation that performs competitively in direct-reward environments. Although investig...
Jan Drugowitsch, Alwyn Barry