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» Learning Generative Models via Discriminative Approaches
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ICCV
2005
IEEE
14 years 9 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
COLT
2006
Springer
13 years 11 months ago
Discriminative Learning Can Succeed Where Generative Learning Fails
Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
Philip M. Long, Rocco A. Servedio
NIPS
2007
13 years 9 months ago
Combined discriminative and generative articulated pose and non-rigid shape estimation
Estimation of three-dimensional articulated human pose and motion from images is a central problem in computer vision. Much of the previous work has been limited by the use of cru...
Leonid Sigal, Alexandru O. Balan, Michael J. Black
ECML
2005
Springer
14 years 1 months ago
Multi-view Discriminative Sequential Learning
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
Ulf Brefeld, Christoph Büscher, Tobias Scheff...
ICIAP
2009
ACM
14 years 8 months ago
A New Generative Feature Set Based on Entropy Distance for Discriminative Classification
Abstract. Score functions induced by generative models extract fixeddimensions feature vectors from different-length data observations by subsuming the process of data generation, ...
Alessandro Perina, Marco Cristani, Umberto Castell...