Projection learning models

Kar Ann Toh; Andrew Beng Jin Teoh

doi:10.1109/ICIEA.2008.4582899

Projection learning models

Kar Ann Toh, Andrew Beng Jin Teoh

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper proposes a learning framework based on projection. Essentially, the learning framework exploits the advantages of linear learning paradigms for regression and classification applications. By incorporating appropriate nonlinear basis or embedding functions, the projection learning framework can be applied to learn arbitrary functions. Several preliminary case studies are provided to evident the behavior of a few specific projection models.

Original language	English
Title of host publication	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Pages	2151-2155
Number of pages	5
DOIs	https://doi.org/10.1109/ICIEA.2008.4582899
Publication status	Published - 2008
Event	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore Duration: 2008 Jun 3 → 2008 Jun 5

Publication series

Name	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Other

Other	2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Country/Territory	Singapore
City	Singapore
Period	08/6/3 → 08/6/5

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Industrial and Manufacturing Engineering

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10.1109/ICIEA.2008.4582899

Cite this

@inproceedings{fca3c224805748bc93e344887bb91760,

title = "Projection learning models",

abstract = "This paper proposes a learning framework based on projection. Essentially, the learning framework exploits the advantages of linear learning paradigms for regression and classification applications. By incorporating appropriate nonlinear basis or embedding functions, the projection learning framework can be applied to learn arbitrary functions. Several preliminary case studies are provided to evident the behavior of a few specific projection models.",

author = "Toh, {Kar Ann} and Teoh, {Andrew Beng Jin}",

year = "2008",

doi = "10.1109/ICIEA.2008.4582899",

language = "English",

isbn = "9781424417186",

series = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",

pages = "2151--2155",

booktitle = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",

note = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 ; Conference date: 03-06-2008 Through 05-06-2008",

}

Toh, KA & Teoh, ABJ 2008, Projection learning models. in 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008., 4582899, 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, pp. 2151-2155, 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, Singapore, Singapore, 08/6/3. https://doi.org/10.1109/ICIEA.2008.4582899

TY - GEN

T1 - Projection learning models

AU - Toh, Kar Ann

AU - Teoh, Andrew Beng Jin

PY - 2008

Y1 - 2008

N2 - This paper proposes a learning framework based on projection. Essentially, the learning framework exploits the advantages of linear learning paradigms for regression and classification applications. By incorporating appropriate nonlinear basis or embedding functions, the projection learning framework can be applied to learn arbitrary functions. Several preliminary case studies are provided to evident the behavior of a few specific projection models.

AB - This paper proposes a learning framework based on projection. Essentially, the learning framework exploits the advantages of linear learning paradigms for regression and classification applications. By incorporating appropriate nonlinear basis or embedding functions, the projection learning framework can be applied to learn arbitrary functions. Several preliminary case studies are provided to evident the behavior of a few specific projection models.

UR - http://www.scopus.com/inward/record.url?scp=51949119542&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51949119542&partnerID=8YFLogxK

U2 - 10.1109/ICIEA.2008.4582899

DO - 10.1109/ICIEA.2008.4582899

M3 - Conference contribution

AN - SCOPUS:51949119542

SN - 9781424417186

T3 - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

SP - 2151

EP - 2155

BT - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

T2 - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Y2 - 3 June 2008 through 5 June 2008

ER -

Projection learning models

Abstract

Publication series

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All Science Journal Classification (ASJC) codes

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