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» Learning subspace kernels for classification
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CIVR
2006
Springer
121views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Finding Faces in Gray Scale Images Using Locally Linear Embeddings
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial exp...
Samuel Kadoury, Martin D. Levine
MCS
2000
Springer
13 years 11 months ago
Combining Fisher Linear Discriminants for Dissimilarity Representations
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
Elzbieta Pekalska, Marina Skurichina, Robert P. W....
CICLING
2010
Springer
13 years 11 months ago
ETL Ensembles for Chunking, NER and SRL
We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Baggin...
Cícero Nogueira dos Santos, Ruy Luiz Milidi...
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 1 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
ICML
2007
IEEE
14 years 8 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...