Florian T. Pokorny
Assistant Professor, School of Computer Science and Communication, KTH Royal Institute of TechnologyThe Path Kernel
In ICPRAM: International Conference on Pattern Recognition Applications and Methods, 2013
Abstract
Kernel methods have been used very successfully to classify data in various application domains. Traditionally,
kernels have been constructed mainly for vectorial data defined on a specific vector space. Much less work has
been addressing the development of kernel functions for non-vectorial data. In this paper, we present a new
kernel for encoding sequential data. We present our results comparing the proposed kernel to the state of the
art, showing a significant improvement in classification and a much improved robustness and interpretability.
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@incollection{baisero2013a,
title = {The Path Kernel},
author = {Baisero, Andrea and Pokorny, Florian T. and Kragic, Danica and Ek, Carl Henrik},
booktitle = {ICPRAM: International Conference on Pattern Recognition Applications and Methods},
year = {2013},
url = {http://www.csc.kth.se/~fpokorny/static/publications/baisero2013a.pdf},
}