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» On learning algorithm selection for classification
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ICTAI
2010
IEEE
15 years 4 months ago
Obtaining Bipartitions from Score Vectors for Multi-Label Classification
Multi-label classification is a popular learning task. However, some of the algorithms that learn from multi-label data, can only output a score for each label, so they cannot be r...
Marios Ioannou, George Sakkas, Grigorios Tsoumakas...
NN
2008
Springer
201views Neural Networks» more  NN 2008»
15 years 6 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
ICML
2007
IEEE
16 years 7 months ago
Non-isometric manifold learning: analysis and an algorithm
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
Piotr Dollár, Serge J. Belongie, Vincent Ra...
ICIAP
1999
ACM
15 years 10 months ago
Methods for Dynamic Classifier Selection
In the field of pattern recognition, the concept of Multiple Classifier Systems (MCSs) was proposed as a method for the development of high performance classification systems. At ...
Giorgio Giacinto, Fabio Roli
TSP
2010
15 years 1 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...