Title :
A Novel Metric Learning Method and Its Application
Author :
Khadir, A. Shaik Abdul ; Raja, S. V Kasmir ; Amanullah, K. Mohamed
Author_Institution :
Dept. of Comp. Sci., Khadir Mohideen Coll., Adirampattinam, India
Abstract :
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis distance, we define locally smooth metrics using local affine transformations which are more flexible. Experimental results provide empirical evidence for the effectiveness of our approach.
Keywords :
content-based retrieval; learning (artificial intelligence); least squares approximations; content-based image retrieval; global Mahalanobis distance; local affine transformations; locally smooth metrics; metric learning method; nonlinear dimensionality reduction; regularized moving least squares; topological structures; Clustering algorithms; Content based retrieval; Educational institutions; Image retrieval; Learning systems; Least squares methods; Machine learning; Optimization methods; Semisupervised learning; Telecommunication computing; Content based image retrieval; Mehalanobis metrics; Semi supervised learning;
Conference_Titel :
Advances in Computing, Control, & Telecommunication Technologies, 2009. ACT '09. International Conference on
Conference_Location :
Trivandrum, Kerala
Print_ISBN :
978-1-4244-5321-4
Electronic_ISBN :
978-0-7695-3915-7
DOI :
10.1109/ACT.2009.209
