Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data

Yi Guo; Junbin Gao; Paul Hing Kwan

doi:10.1007/978-3-540-76928-6_71

Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data

Yi Guo, Junbin Gao, Paul Hing Kwan

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

Abstract

This paper proposes a new nonlinear dimensionality reduction algorithm called RCTKE for highly structured data. It is built on the original TKE by incorporating a mapping function into the objective functional of TKE as regularization terms where the mapping function can be learned from training data and be used for novel samples. The experimental results on highly structured data is used to verify the effectiveness of the algorithm.

Original language	English
Title of host publication	AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007
Editors	Orgun, Mehmet A, Thornton, J
Place of Publication	Berlin, Germany
Publisher	Springer
Pages	659-663
ISBN (Print)	9783540769262
DOIs	https://doi.org/10.1007/978-3-540-76928-6_71
Publication status	Published - 2007
Event	AI 2007: 20th Australian Joint Conference on Artificial Intelligence - Gold Coast, Australia Duration: 2 Dec 2007 → 6 Dec 2007

Conference

Conference	AI 2007: 20th Australian Joint Conference on Artificial Intelligence
City	Gold Coast, Australia
Period	2/12/07 → 6/12/07

Keywords

Pattern Recognition and Data Mining

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10.1007/978-3-540-76928-6_71

https://hdl.handle.net/1959.11/4513

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Guo, Y., Gao, J., & Kwan, P. H. (2007). Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. In Orgun, M. A, Thornton, & J (Eds.), AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007 (pp. 659-663). Springer. https://doi.org/10.1007/978-3-540-76928-6_71

Guo, Yi ; Gao, Junbin ; Kwan, Paul Hing. / Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007. editor / Orgun ; Mehmet A ; Thornton ; J. Berlin, Germany : Springer, 2007. pp. 659-663

@inproceedings{6231446ccca949b0b092020f9ed8d1d2,

title = "Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data",

abstract = "This paper proposes a new nonlinear dimensionality reduction algorithm called RCTKE for highly structured data. It is built on the original TKE by incorporating a mapping function into the objective functional of TKE as regularization terms where the mapping function can be learned from training data and be used for novel samples. The experimental results on highly structured data is used to verify the effectiveness of the algorithm.",

keywords = "Pattern Recognition and Data Mining",

author = "Yi Guo and Junbin Gao and Kwan, \{Paul Hing\}",

year = "2007",

doi = "10.1007/978-3-540-76928-6\_71",

language = "English",

isbn = "9783540769262",

pages = "659--663",

editor = "Orgun and Mehmet A and Thornton and J",

booktitle = "AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007",

publisher = "Springer",

note = "AI 2007: 20th Australian Joint Conference on Artificial Intelligence ; Conference date: 02-12-2007 Through 06-12-2007",

}

Guo, Y, Gao, J & Kwan, PH 2007, Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. in Orgun, M A, Thornton & J (eds), AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007. Springer, Berlin, Germany, pp. 659-663, AI 2007: 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, 2/12/07. https://doi.org/10.1007/978-3-540-76928-6_71

Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. / Guo, Yi; Gao, Junbin; Kwan, Paul Hing.
AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007. ed. / Orgun; Mehmet A; Thornton; J. Berlin, Germany: Springer, 2007. p. 659-663.

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

TY - GEN

T1 - Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data

AU - Guo, Yi

AU - Gao, Junbin

AU - Kwan, Paul Hing

PY - 2007

Y1 - 2007

N2 - This paper proposes a new nonlinear dimensionality reduction algorithm called RCTKE for highly structured data. It is built on the original TKE by incorporating a mapping function into the objective functional of TKE as regularization terms where the mapping function can be learned from training data and be used for novel samples. The experimental results on highly structured data is used to verify the effectiveness of the algorithm.

AB - This paper proposes a new nonlinear dimensionality reduction algorithm called RCTKE for highly structured data. It is built on the original TKE by incorporating a mapping function into the objective functional of TKE as regularization terms where the mapping function can be learned from training data and be used for novel samples. The experimental results on highly structured data is used to verify the effectiveness of the algorithm.

KW - Pattern Recognition and Data Mining

UR - https://www.scopus.com/pages/publications/38349068706

U2 - 10.1007/978-3-540-76928-6_71

DO - 10.1007/978-3-540-76928-6_71

M3 - Conference contribution

SN - 9783540769262

SP - 659

EP - 663

BT - AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007

A2 - Orgun, null

A2 - A, Mehmet

A2 - Thornton, null

A2 - J, null

PB - Springer

CY - Berlin, Germany

T2 - AI 2007: 20th Australian Joint Conference on Artificial Intelligence

Y2 - 2 December 2007 through 6 December 2007

ER -

Guo Y, Gao J, Kwan PH. Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. In Orgun, A M, Thornton, J, editors, AI 2007: Advances in Artificial Intelligence: Proceedings of the 20th Australian Joint Conference on Artificial Intelligence Gold Coast, Australia, December 2-6, 2007. Berlin, Germany: Springer. 2007. p. 659-663 doi: 10.1007/978-3-540-76928-6_71

Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data

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