@article{8df44b8304a542589235a06761e27850,
title = "Supervised learning of local projection kernels",
abstract = "We formulate a supervised, localized dimensionality reduction method using a gating model that divides up the input space into regions and selects the dimensionality reduction projection separately in each region. The gating model, the locally linear projections, and the kernel-based supervised learning algorithm which uses them in its kernels are coupled and their training is performed with an alternating optimization procedure. Our proposed local projection kernel projects a data instance into different feature spaces by using the local projection matrices, combines them with the gating model, and performs the dot product in the combined feature space. Empirical results on benchmark data sets for visualization and classification tasks validate the idea. The method is generalizable to regression estimation and novelty detection.",
keywords = "Dimensionality reduction, Kernel machines, Local embedding, Subspace learning",
author = "Mehmet G{\"o}nen and Ethem Alpaydn",
note = "Funding Information: This work was supported by the Turkish Academy of Sciences in the framework of the Young Scientist Award Program under EA-T{\"U}BA-GEBİP/2001-1-1, Boğazi{\c c}i University Scientific Research Project 07HA101 and the Scientific and Technological Research Council of Turkey (T{\"U}BİTAK) under Grant EEEAG 107E222. The work of M. G{\"o}nen was supported by the Ph.D. scholarship (2211) from T{\"U}BİTAK. Mehmet G{\"o}nen received the B.Sc. degree in industrial engineering and the M.Sc. degree in computer engineering from Boğazi{\c c}i University, İstanbul, Turkey, in 2003 and 2005, respectively, where he is currently working towards the Ph.D. degree at the Department of Computer Engineering. He is a Teaching Assistant at the Department of Computer Engineering, Boğazi{\c c}i University. His research interests include support vector machines, kernel methods, Bayesian methods, and real-time control and simulation of flexible manufacturing systems. Ethem Alpaydın received his B.Sc. from the Department of Computer Engineering of Boğazi{\c c}i University in 1987 and the degree of Docteur es Sciences from Ecole Polytechnique F{\'e}d{\'e}rale de Lausanne in 1990. He did his postdoctoral work at the International Computer Science Institute, Berkeley, in 1991 and afterwards was appointed as Assistant Professor at the Department of Computer Engineering of Boğazi{\c c}i University. He was promoted to Associate Professor in 1996 and Professor in 2002 in the same department. As visiting researcher, he worked at the Department of Brain and Cognitive Sciences of MIT in 1994, the International Computer Science Institute, Berkeley, in 1997 and IDIAP, Switzerland, in 1998. He was awarded a Fulbright Senior scholarship in 1997 and received the Research Excellence Award from the Boğazi{\c c}i University Foundation in 1998, the Young Scientist Award from the Turkish Academy of Sciences in 2001 and the Scientific Encouragement Award from the Scientific and Technological Research Council of Turkey in 2002. His book Introduction to Machine Learning was published by The MIT Press in October 2004. Its German edition was published in 2008, its Chinese edition in 2009, and its second edition in 2010. Its Turkish edition is in preparation. He is a senior member of the IEEE, an editorial board member of The Computer Journal (Oxford University Press) and an associate editor of Pattern Recognition (Elsevier). ",
year = "2010",
month = jun,
doi = "10.1016/j.neucom.2009.11.043",
language = "English (US)",
volume = "73",
pages = "1694--1703",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",
number = "10-12",
}