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» A general algorithm for data dependence analysis
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PRL
2010
158views more  PRL 2010»
15 years 1 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
15 years 6 months ago
Characterizing large text corpora using a maximum variation sampling genetic algorithm
An enormous amount of information available via the Internet exists. Much of this data is in the form of text-based documents. These documents cover a variety of topics that are v...
Robert M. Patton, Thomas E. Potok
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 3 months ago
Privacy preserving regression modelling via distributed computation
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
131
Voted
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 3 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
PAMI
2008
156views more  PAMI 2008»
15 years 3 months ago
Tied Factor Analysis for Face Recognition across Large Pose Differences
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identi...
Simon J. D. Prince, James H. Elder, Jonathan Warre...