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» Learning Functions from Imperfect Positive Data
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151
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ISDA
2010
IEEE
15 years 1 months ago
Comparing SVM ensembles for imbalanced datasets
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal
164
Voted
IRMA
2000
15 years 5 months ago
A survey of spatial data mining methods databases and statistics point of views
This paper reviews the data mining methods that are combined with Geographic Information Systems (GIS) for carrying out spatial analysis of geographic data. We will first look at d...
Karine Zeitouni
128
Voted
ECCV
2008
Springer
16 years 5 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...
145
Voted
ALT
2004
Springer
16 years 20 days ago
On Kernels, Margins, and Low-Dimensional Mappings
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
Maria-Florina Balcan, Avrim Blum, Santosh Vempala
150
Voted
ICIP
2001
IEEE
16 years 5 months ago
Use of a probabilistic shape model for non-linear registration of 3D scattered data
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...
Isabelle Corouge, Christian Barillot