TPSLVM: a dimensionality reduction algorithm based on thin plate splines
Article
Jiang, X., Gao, J., Wang, T. and Shi, D. 2014. TPSLVM: a dimensionality reduction algorithm based on thin plate splines. IEEE Transactions on Cybernetics. 44 (10), pp. 1795-1807. https://doi.org/10.1109/TCYB.2013.2295329
Type | Article |
---|---|
Title | TPSLVM: a dimensionality reduction algorithm based on thin plate splines |
Authors | Jiang, X., Gao, J., Wang, T. and Shi, D. |
Abstract | Dimensionality reduction (DR) has been considered as one of the most significant tools for data analysis. One type of DR algorithms is based on latent variable models (LVM). LVM-based models can handle the preimage problem easily. In this paper we propose a new LVM-based DR model, named thin plate spline latent variable model (TPSLVM). Compared to the well-known Gaussian process latent variable model (GPLVM), our proposed TPSLVM is more powerful especially when the dimensionality of the latent space is low. Also, TPSLVM is robust to shift and rotation. This paper investigates two extensions of TPSLVM, i.e., the back-constrained TPSLVM (BC-TPSLVM) and TPSLVM with dynamics (TPSLVM-DM) as well as their combination BC-TPSLVM-DM. Experimental results show that TPSLVM and its extensions provide better data visualization and more efficient dimensionality reduction compared to PCA, GPLVM, ISOMAP, etc. |
Research Group | Artificial Intelligence group |
Publisher | IEEE |
Journal | IEEE Transactions on Cybernetics |
ISSN | 2168-2267 |
Electronic | 2168-2275 |
Publication dates | |
01 Oct 2014 | |
Publication process dates | |
Deposited | 03 Jun 2015 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TCYB.2013.2295329 |
Language | English |
https://repository.mdx.ac.uk/item/858w1
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