Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
7
click to vote
ECCV
2004
Springer
favorite
Email
discuss
report
128
views
Computer Vision
»
more
ECCV 2004
»
Kernel Feature Selection with Side Data Using a Spectral Approach
14 years 5 months ago
Download
www.cs.huji.ac.il
Abstract. We address the problem of selecting a subset of the most relevant features from a set of sample data in cases where there are multiple (equally reasonable) solutions. In particular, this topic includes on one
Amnon Shashua, Lior Wolf
Real-time Traffic
Computer Vision
|
ECCV 2004
|
Relevant Features
|
claim paper
Related Content
»
Using Kernel Basis with Relevance Vector Machine for Feature Selection
»
Multiway Spectral Clustering with OutofSample Extensions through Weighted Kernel PCA
»
Constrained Clustering by Spectral Kernel Learning
»
Semisupervised Feature Selection via Spectral Analysis
»
Improving Gaussian processes classification by spectral data reorganizing
»
A Bayesian network approach to feature selection in mass spectrometry data
»
Feature Selection for Nonlinear Kernel Support Vector Machines
»
Feature Selection for Value Function Approximation Using Bayesian Model Selection
»
Feature Selection for Density LevelSets
more »
Post Info
More Details (n/a)
Added
15 Oct 2009
Updated
15 Oct 2009
Type
Conference
Year
2004
Where
ECCV
Authors
Amnon Shashua, Lior Wolf
Comments
(0)
Researcher Info
Computer Vision Study Group
Computer Vision