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92
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ICML
2005
IEEE
15 years 11 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
75
Voted
ITICSE
2004
ACM
15 years 3 months ago
Generation as method for explorative learning in computer science education
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advant...
Andreas Kerren
ICML
2005
IEEE
15 years 11 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
CEC
2010
IEEE
14 years 11 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
95
Voted
ICDAR
2009
IEEE
15 years 5 months ago
Graphic Symbol Recognition Using Graph Based Signature and Bayesian Network Classifier
We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image an...
Muhammad Muzzamil Luqman, Thierry Brouard, Jean-Yv...