@inproceedings{d36ee12046c34b45aa0e7817c3d63ee3,
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.",
author = "Yi Guo and Junbin Gao and Kwan, \{Paul W.\}",
year = "2007",
doi = "10.1007/978-3-540-76928-6\_71",
language = "English",
isbn = "9783540769262",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "659--663",
booktitle = "AI 2007",
note = "20th Australian Joint Conference on Artificial Intelligence, AI 2007 ; Conference date: 02-12-2007 Through 06-12-2007",
}