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CVPR
2001
IEEE
14 years 9 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
ECML
2006
Springer
13 years 11 months ago
Margin-Based Active Learning for Structured Output Spaces
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dan Roth, Kevin Small
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
CVPR
2009
IEEE
15 years 2 months ago
Volterrafaces: Discriminant Analysis using Volterra Kernels
In this paper we present a novel face classification system where we represent face images as a spatial arrangement of image patches, and seek a smooth non-linear functional map...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri
ESANN
2006
13 years 9 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...