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ECAI
2006
Springer
15 years 6 months ago
Patch Learning for Incremental Classifier Design
We present a learning algorithm for nominal data. It builds a classifier by adding iteratively a simple patch function that modifies the current classifier. Its main advantage lies...
Rudy Sicard, Thierry Artières, Eric Petit
CVPR
2001
IEEE
16 years 4 months ago
Bayesian Learning of Sparse Classifiers
Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
Anil K. Jain, Mário A. T. Figueiredo
AI
2002
Springer
15 years 2 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
JMLR
2010
185views more  JMLR 2010»
14 years 9 months ago
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Franz Pernkopf, Jeff A. Bilmes
ICDM
2009
IEEE
162views Data Mining» more  ICDM 2009»
15 years 2 days ago
Towards a Universal Text Classifier: Transfer Learning Using Encyclopedic Knowledge
Document classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifie...
Pu Wang, Carlotta Domeniconi