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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 1 months ago
Assessing data mining results via swap randomization
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
BMCBI
2007
160views more  BMCBI 2007»
15 years 25 days ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
113
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BMCBI
2010
118views more  BMCBI 2010»
15 years 25 days ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
112
Voted
WCE
2007
15 years 1 months ago
Performance Modelling of the Computational Hardware: A Statistical Approach
—This paper proposes and uses multivariate methods as a tool to evaluate performances of the hardware of microcomputers using their performance data, speed and price. The evaluat...
Ibrahim Akman, Yasar Yesilcay
105
Voted
IJCAI
2003
15 years 2 months ago
Spectral Learning
We present a simple, easily implemented spectral learning algorithm which applies equally whether we have no supervisory information, pairwise link constraints, or labeled example...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...