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» On learning algorithm selection for classification
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ICML
1996
IEEE
15 years 10 months ago
Discovering Structure in Multiple Learning Tasks: The TC Algorithm
Recently, there has been an increased interest in "lifelong" machine learning methods, that transfer knowledge across multiple learning tasks. Such methods have repeated...
Sebastian Thrun, Joseph O'Sullivan
ICML
2004
IEEE
16 years 7 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
PAMI
2006
215views more  PAMI 2006»
15 years 6 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
ICML
2007
IEEE
16 years 7 months ago
Support cluster machine
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Bin Li, Mingmin Chi, Jianping Fan, Xiangyang Xue
ICCV
2005
IEEE
16 years 8 months ago
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
Kristen Grauman, Trevor Darrell