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» Evaluating Feature Selection for SVMs in High Dimensions
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SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 21 days ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
KDD
2001
ACM
196views Data Mining» more  KDD 2001»
15 years 10 months ago
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
Cheng Yang, Usama M. Fayyad, Paul S. Bradley
VLDB
1999
ACM
118views Database» more  VLDB 1999»
15 years 2 months ago
Similarity Search in High Dimensions via Hashing
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing ...
Aristides Gionis, Piotr Indyk, Rajeev Motwani
ICIP
2010
IEEE
14 years 8 months ago
Fast pedestrian detection with multi-scale orientation features and two-stage classifiers
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO...
Qixiang Ye, Jianbin Jiao, Baochang Zhang
ICIAP
2005
ACM
15 years 10 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...