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» Feature Selection for Support Vector Machines
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ICIP
2003
IEEE
14 years 9 months ago
Classification-based spatial error concealment for images
* This paper presents a new, classification-based spatial error concealment algorithm for images. The proposed scheme takes advantage of two state-of-the-art concealment schemes an...
M. Chen, M. Wu, Y. Zheng
ESANN
2007
13 years 9 months ago
One-class SVM regularization path and comparison with alpha seeding
One-class support vector machines (1-SVMs) estimate the level set of the underlying density observed data. Aside the kernel selection issue, one difficulty concerns the choice of t...
Alain Rakotomamonjy, Manuel Davy
PKDD
2009
Springer
135views Data Mining» more  PKDD 2009»
14 years 2 months ago
Syntactic Structural Kernels for Natural Language Interfaces to Databases
A core problem in data mining is to retrieve data in a easy and human friendly way. Automatically translating natural language questions into SQL queries would allow for the design...
Alessandra Giordani, Alessandro Moschitti
BMCBI
2008
158views more  BMCBI 2008»
13 years 8 months ago
Real value prediction of protein solvent accessibility using enhanced PSSM features
Background: Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from...
Darby Tien-Hao Chang, Hsuan-Yu Huang, Yu-Tang Syu,...
IS
2007
13 years 7 months ago
A co-training framework for searching XML documents
In this paper, we study the use of XML tagged keywords (or simply key-tags) to search an XML fragment in a collection of XML documents. We present techniques that are able to empl...
Wilfred Ng, Ho Lam Lau