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» On the Comparability of Software Clustering Algorithms
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BMCBI
2006
124views more  BMCBI 2006»
13 years 8 months ago
Predicting transcription factor binding sites using local over-representation and comparative genomics
Background: Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented tran...
Matthieu Defrance, Hélène Touzet
JMLR
2010
211views more  JMLR 2010»
13 years 2 months ago
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Bo Dai, Baogang Hu
SEMCO
2007
IEEE
14 years 2 months ago
Clustering Using Feature Domain Similarity to Discover Word Senses for Adjectives
This paper presents a new clustering algorithm called DSCBC which is designed to automatically discover word senses for polysemous words. DSCBC is an extension of CBC Clustering [...
Noriko Tomuro, Steven L. Lytinen, Kyoko Kanzaki, H...
SSDBM
2006
IEEE
123views Database» more  SSDBM 2006»
14 years 1 months ago
Mining Hierarchies of Correlation Clusters
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
Elke Achtert, Christian Böhm, Peer Kröge...
VLSISP
2011
358views Database» more  VLSISP 2011»
13 years 2 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...