In this paper, we propose the distributed tree kernels (DTK) as a novel method to reduce time and space complexity of tree kernels. Using a linear complexity algorithm to compute vectors for trees, we embed feature spaces of tree fragments in low-dimensional spaces where the kernel computation is directly done with dot product. We show that DTKs are faster, correlate with tree kernels, and obtain a statistically similar performance in two natural language processing tasks.
Zanzotto, F.m., Dell'Arciprete, L. (2012). Distributed Tree Kernels. In Proceedings of International Conference on Machine Learning (ICML) - http://www.scimagojr.com/journalsearch.php?q=21100217201&tip=sid&clean=0 (GGS Conference Rating 1 A++) (pp.--).
Distributed Tree Kernels
ZANZOTTO, FABIO MASSIMO;
2012-01-01
Abstract
In this paper, we propose the distributed tree kernels (DTK) as a novel method to reduce time and space complexity of tree kernels. Using a linear complexity algorithm to compute vectors for trees, we embed feature spaces of tree fragments in low-dimensional spaces where the kernel computation is directly done with dot product. We show that DTKs are faster, correlate with tree kernels, and obtain a statistically similar performance in two natural language processing tasks.| File | Dimensione | Formato | |
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