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» Unsupervised Feature Selection Using Feature Similarity
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ICMLA
2008
14 years 2 days ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
ICML
2008
IEEE
14 years 11 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
TMI
2002
155views more  TMI 2002»
13 years 10 months ago
Active Shape Model Segmentation with Optimal Features
Abstract--An active shape model segmentation scheme is presented that is steered by optimal local features, contrary to normalized first order derivative profiles, as in the origin...
Bram van Ginneken, Alejandro F. Frangi, Joes Staal...
CVPR
2012
IEEE
12 years 1 months ago
Beyond spatial pyramids: Receptive field learning for pooled image features
In this paper we examine the effect of receptive field designs on classification accuracy in the commonly adopted pipeline of image classification. While existing algorithms us...
Yangqing Jia, Chang Huang, Trevor Darrell
VLDB
2000
ACM
121views Database» more  VLDB 2000»
14 years 2 months ago
Optimizing Multi-Feature Queries for Image Databases
In digital libraries image retrieval queries can be based on the similarity of objects, using several feature attributes like shape, texture, color or text. Such multi-feature que...
Ulrich Güntzer, Wolf-Tilo Balke, Werner Kie&s...