NDLI: Multi-scale Support Vector Regression

Content Provider	IEEE Xplore Digital Library
Author	Ferrari, S. Bellocchio, F. Piuri, V. Borghese, N.A.
Copyright Year	2010
Description	Author affiliation: Department of Information Technology, Università degli Studi di Milano, Italy (Ferrari, S.; Bellocchio, F.; Piuri, V.) \|\| Department of Computer Science, Università degli Studi di Milano, Italy (Borghese, N.A.)
Abstract	A multi-kernel Support Vector Machine model, called Hierarchical Support Vector Regression (HSVR), is proposed here. This is a self-organizing (by growing) multiscale version of a Support Vector Regression (SVR) model. It is constituted of hierarchical layers, each containing a standard SVR with Gaussian kernel, at decreasing scales. HSVR have been applied to a noisy synthetic dataset. The results illustrate their power in denoising the original data, obtaining an effective multiscale reconstruction of better quality than that obtained by standard SVR. Furthermore with this approach the well known problem of tuning the SVR parameters is strongly simplified.
Starting Page	1
Ending Page	7
File Size	849725
Page Count	7
File Format	PDF
ISBN	9781424469161
ISSN	10987576
e-ISBN	9781424469185
DOI	10.1109/IJCNN.2010.5596630
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-18
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Support vector machines Training Optimization Accuracy Computational modeling Approximation methods Kernel functions Support Vector Machine Support Vector Regression
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Multi-scale linear programming support vector regression for ethylene distillation modeling.

Multi-scale Least Square Wavelet Support Vector Machine

Fast regularized kernel function approximation

Accelerated training of support vector machines

Application of Multi-scale Wavelet Kernel in Traffic Flow Forecasting

The differential approximation method to determine a scale parameter interval for a multi-scale Gaussian kernel RVM regression

Particle Swarm Optimization-Least Squares Support Vector Regression with Multi-scale Wavelet Kernel

Distributed kernel learning using Kernel Recursive Least Squares

A comparative study of relevant vector machine and support vector machine in uncertainty analysis

Multi-scale Support Vector Regression

Similar Documents

Multi-scale linear programming support vector regression for ethylene distillation modeling.

Multi-scale Least Square Wavelet Support Vector Machine

Fast regularized kernel function approximation

Accelerated training of support vector machines

Application of Multi-scale Wavelet Kernel in Traffic Flow Forecasting

The differential approximation method to determine a scale parameter interval for a multi-scale Gaussian kernel RVM regression

Particle Swarm Optimization-Least Squares Support Vector Regression with Multi-scale Wavelet Kernel

Distributed kernel learning using Kernel Recursive Least Squares

A comparative study of relevant vector machine and support vector machine in uncertainty analysis

Multi-scale Support Vector Regression