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» Optimization on Support Vector Machines
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ICASSP
2011
IEEE
14 years 2 months ago
On the design of matched orthonormal wavelets with compact support
We develop new algorithms for designing matched wavelets and matched scaling functions using a new parametrization of compactly supported orthonormal wavelets that is developed in...
Mohamed F. Mansour
CIDM
2007
IEEE
15 years 2 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
CVPR
2010
IEEE
14 years 10 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
BMCBI
2008
93views more  BMCBI 2008»
14 years 10 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
ICDE
2005
IEEE
103views Database» more  ICDE 2005»
15 years 11 months ago
Vectorizing and Querying Large XML Repositories
Vertical partitioning is a well-known technique for optimizing query performance in relational databases. An extreme form of this technique, which we call vectorization, is to sto...
Peter Buneman, Byron Choi, Wenfei Fan, Robert Hutc...