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» Classes and clusters in data analysis
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120
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MA
2010
Springer
153views Communications» more  MA 2010»
15 years 3 months ago
Testing quasi-independence for truncation data
Quasi-independence is a common assumption for analyzing truncated data. To verify this condition, we consider a class of weighted log-rank type statistics that include existing te...
Takeshi Emura, Weijing Wang
COMSIS
2010
15 years 2 months ago
Effective semi-supervised nonlinear dimensionality reduction for wood defects recognition
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
Zhao Zhang, Ning Ye
BMCBI
2010
182views more  BMCBI 2010»
15 years 4 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
129
Voted
CISS
2008
IEEE
15 years 11 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
TIT
1998
96views more  TIT 1998»
15 years 4 months ago
Sequential Prediction of Individual Sequences Under General Loss Functions
Abstract— We consider adaptive sequential prediction of arbitrary binary sequences when the performance is evaluated using a general loss function. The goal is to predict on each...
David Haussler, Jyrki Kivinen, Manfred K. Warmuth