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» Structured metric learning for high dimensional problems
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CVPR
2010
IEEE
14 years 10 months ago
Exploiting Monge structures in optimum subwindow search
Optimum subwindow search for object detection aims to find a subwindow so that the contained subimage is most similar to the query object. This problem can be formulated as a fou...
Senjian An, Patrick Peursum, Wanquan Liu, Svetha V...
ICIP
2008
IEEE
15 years 11 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
14 years 8 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
13 years 5 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
MCS
2001
Springer
15 years 2 months ago
Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many machine learning problems [4, 16]. However, the exten...
Nikunj C. Oza, Kagan Tumer