Summary: Journal of Machine Learning Research 10 (2009) 935-975 Submitted 8/08; Revised 1/09; Published 4/09
Nonextensive Information Theoretic Kernels on Measures
Andr´e F. T. Martins AFM@CS.CMU.EDU
Noah A. Smith NASMITH@CS.CMU.EDU
Eric P. Xing EPXING@CS.CMU.EDU
School of Computer Science
Carnegie Mellon University
Pittsburgh, PA, USA
Pedro M. Q. Aguiar AGUIAR@ISR.IST.UTL.PT
Instituto de Sistemas e Rob´otica
Instituto Superior T´ecnico
Lisboa, Portugal
M´ario A. T. Figueiredo MARIO.FIGUEIREDO@LX.IT.PT
Instituto de Telecomunicac¸~oes
Instituto Superior T´ecnico
Lisboa, Portugal
Editor: Francis Bach
Abstract
Positive definite kernels on probability measures have been recently applied to classification prob-
lems involving text, images, and other types of structured data. Some of these kernels are related

Source: Aguiar, Pedro M. Q. - Institute for Systems and Robotics (Lisbon)
Xing, Eric P. - School of Computer Science, Carnegie Mellon University

Collections: Computer Technologies and Information Sciences; Engineering