# The Path Kernel

Andrea Baisero, Florian T. Pokorny, Danica Kragic, Carl Henrik Ek
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.

## Files

@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}, }