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» A Fully Distributed Framework for Cost-Sensitive Data Mining
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139
Voted
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 4 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
IBPRIA
2007
Springer
15 years 9 months ago
Optimally Discriminant Moments for Speckle Detection in Real B-Scan Images
Detection of speckle in ultrasound (US) images has been regarded as an important research topic in US imaging, mainly focusing on two specific applications: improving signal to no...
Robert Marti, Joan Martí, Jordi Freixenet, ...
131
Voted
IPPS
2008
IEEE
15 years 10 months ago
Providing security to the Desktop Data Grid
Volunteer Computing is becoming a new paradigm not only for the Computational Grid, but also for institutions using production-level Data Grids because of the enormous storage pot...
Jesus Luna, Michail Flouris, Manolis Marazakis, An...
140
Voted
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 4 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
154
Voted
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 4 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan