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» Generalization Improvement in Multi-Objective Learning
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94
Voted
WWW
2008
ACM
16 years 1 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
KDD
2009
ACM
142views Data Mining» more  KDD 2009»
16 years 1 months ago
Quantification and semi-supervised classification methods for handling changes in class distribution
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Jack Chongjie Xue, Gary M. Weiss
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 1 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
108
Voted
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 1 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
111
Voted
ICSE
2007
IEEE-ACM
16 years 21 days ago
Software Development Environments for Scientific and Engineering Software: A Series of Case Studies
The need for high performance computing applications for computational science and engineering projects is growing rapidly, yet there have been few detailed studies of the softwar...
Jeffrey C. Carver, Richard P. Kendall, Susan E. Sq...