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IJCAI
2003
13 years 11 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
ICML
2002
IEEE
14 years 10 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
CEAS
2007
Springer
14 years 2 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 8 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
ICDM
2009
IEEE
165views Data Mining» more  ICDM 2009»
13 years 7 months ago
Audio Classification of Bird Species: A Statistical Manifold Approach
Our goal is to automatically identify which species of bird is present in an audio recording using supervised learning. Devising effective algorithms for bird species classificati...
Forrest Briggs, Raviv Raich, Xiaoli Z. Fern