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KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 5 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
16 years 5 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
KDD
2006
ACM
159views Data Mining» more  KDD 2006»
16 years 5 months ago
Global distance-based segmentation of trajectories
This work introduces distance-based criteria for segmentation of object trajectories. Segmentation leads to simplification of the original objects into smaller, less complex primi...
Aris Anagnostopoulos, Michail Vlachos, Marios Hadj...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 5 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...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
16 years 5 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
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