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87
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ICML
2003
IEEE
16 years 2 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
CVPR
2004
IEEE
16 years 3 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
VMV
2008
107views Visualization» more  VMV 2008»
15 years 3 months ago
Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Erik Rodner, Joachim Denzler
BMCBI
2010
116views more  BMCBI 2010»
15 years 2 months ago
FiGS: a filter-based gene selection workbench for microarray data
Background: The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene sel...
Taeho Hwang, Choong-Hyun Sun, Taegyun Yun, Gwan-Su...
121
Voted
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
15 years 1 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...