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» Choosing Multiple Parameters for Support Vector Machines
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CDC
2009
IEEE
159views Control Systems» more  CDC 2009»
14 years 17 days ago
A distributed machine learning framework
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
Tansu Alpcan, Christian Bauckhage
VIS
2007
IEEE
162views Visualization» more  VIS 2007»
14 years 9 months ago
Segmentation of Three-dimensional Retinal Image Data
We have combined methods from volume visualization and data analysis to support better diagnosis and treatment of human retinal diseases. Many diseases can be identified by abnorma...
Alfred R. Fuller, Rober t J. Zawadzki, Stacey Ch...
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
ICML
2008
IEEE
14 years 8 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
MM
2010
ACM
251views Multimedia» more  MM 2010»
13 years 8 months ago
A cognitive approach for effective coding and transmission of 3D video
Reliable delivery of 3D video contents to a wide set of users is expected to be the next big revolution in multimedia applications provided that it is possible to grant a certain ...
Simone Milani, Giancarlo Calvagno