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FOCS
2004
IEEE
15 years 7 months ago
Learning with Errors in Answers to Membership Queries
We study the learning models defined in [AKST97]: Learning with equivalence and limited membership queries and learning with equivalence and malicious membership queries. We show ...
Laurence Bisht, Nader H. Bshouty, Lawrance Khoury
AAAI
2006
15 years 5 months ago
A Fast Decision Tree Learning Algorithm
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast ...
Jiang Su, Harry Zhang
CVPR
2009
IEEE
16 years 11 months ago
Unsupervised Learning for Graph Matching
Graph matching is an important problem in computer vision. It is used in 2D and 3D object matching and recognition. Despite its importance, there is little literature on learnin...
Marius Leordeanu, Martial Hebert
150
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ICPR
2000
IEEE
16 years 5 months ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
ISBI
2008
IEEE
16 years 4 months ago
Learning non-homogenous textures and the unlearning problem with application to drusen detection in retinal images
In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
Noah Lee, Andrew F. Laine, Theodore R. Smith