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» Learning with Idealized Kernels
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CONEXT
2007
ACM
15 years 5 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
ICML
2007
IEEE
16 years 4 months ago
Discriminative learning for differing training and test distributions
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
Michael Brückner, Steffen Bickel, Tobias Sche...
FSMNLP
2008
Springer
15 years 5 months ago
Learning with Weighted Transducers
Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine ...
Corinna Cortes, Mehryar Mohri
ICCV
2009
IEEE
16 years 9 months ago
Robust Fitting of Multiple Structures: The Statistical Learning Approach
We propose an unconventional but highly effective approach to robust fitting of multiple structures by using statistical learning concepts. We design a novel Mercer kernel for t...
Tat-Jun Chin, Hanzi Wang, David Suter
ICIP
2009
IEEE
15 years 1 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu