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» Experimental perspectives on learning from imbalanced data
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SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
14 years 11 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
IJON
2010
181views more  IJON 2010»
14 years 8 months ago
Active learning with extremely sparse labeled examples
An active learner usually assumes there are some labeled data available based on which a moderate classifier is learned and then examines unlabeled data to manually label the mos...
Shiliang Sun, David R. Hardoon
MCS
2005
Springer
15 years 3 months ago
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
Abstract. Obtaining ground truth for hyperspectral data is an expensive task. In addition, a number of factors cause the spectral signatures of the same class to vary with location...
Suju Rajan, Joydeep Ghosh
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
ECAI
2006
Springer
15 years 1 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani