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» Learning SVMs from Sloppily Labeled Data
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CVPR
2004
IEEE
14 years 11 months ago
Multiscale Conditional Random Fields for Image Labeling
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a p...
Miguel Á. Carreira-Perpiñán, ...
CIKM
2009
Springer
14 years 3 months ago
Automatic link detection: a sequence labeling approach
The popularity of Wikipedia and other online knowledge bases has recently produced an interest in the machine learning community for the problem of automatic linking. Automatic hy...
James J. Gardner, Li Xiong
ICMLA
2007
13 years 10 months ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis
ICPR
2006
IEEE
14 years 10 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
MLG
2007
Springer
14 years 3 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich