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» Robustness of the Learning with Errors Assumption
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CVPR
2004
IEEE
16 years 1 months ago
Visual Tracking Using Learned Linear Subspaces
This paper presents a simple but robust visual tracking algorithm based on representing the appearances of objects using affine warps of learned linear subspaces of the image spac...
Jeffrey Ho, Kuang-Chih Lee, Ming-Hsuan Yang, David...
SCALESPACE
2007
Springer
15 years 5 months ago
Space-Time Segmentation Based on a Joint Entropy with Estimation of Nonparametric Distributions
This paper deals with video segmentation based on motion and spatial information. Classically, the nucleus of the motion term is the motion compensation error (MCE) between two con...
Ariane Herbulot, Sylvain Boltz, Eric Debreuve, Mic...
CVPR
2006
IEEE
16 years 1 months ago
Modeling Correspondences for Multi-Camera Tracking Using Nonlinear Manifold Learning and Target Dynamics
Multi-camera tracking systems often must maintain consistent identity labels of the targets across views to recover 3D trajectories and fully take advantage of the additional info...
Vlad I. Morariu, Octavia I. Camps
ACML
2009
Springer
15 years 4 months ago
Learning Algorithms for Domain Adaptation
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Manas A. Pathak, Eric Nyberg
ML
2007
ACM
153views Machine Learning» more  ML 2007»
14 years 11 months ago
Multi-Class Learning by Smoothed Boosting
AdaBoost.OC has been shown to be an effective method in boosting “weak” binary classifiers for multi-class learning. It employs the Error-Correcting Output Code (ECOC) method ...
Rong Jin, Jian Zhang 0003