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» PAC-Bayesian learning of linear classifiers
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FLAIRS
2008
13 years 10 months ago
Selecting Minority Examples from Misclassified Data for Over-Sampling
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Jorge de la Calleja, Olac Fuentes, Jesús Go...
CVPR
2010
IEEE
13 years 10 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
SI3D
2006
ACM
14 years 1 months ago
Human motion estimation from a reduced marker set
Motion capture data from human subjects exhibits considerable redundancy. In this paper, we propose novel methods for exploiting this redundancy. In particular, we set out to find...
Guodong Liu, Jingdan Zhang, Wei Wang 0010, Leonard...
NIPS
1997
13 years 9 months ago
Learning to Order Things
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
William W. Cohen, Robert E. Schapire, Yoram Singer
CONEXT
2007
ACM
13 years 9 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek