Abstract
We show how a family of exact solutions to the Recursive Principal Components Analysis learning problem can be computed for sequences and tree structured inputs. These solutions are derived from eigenanalysis of extended vectorial representations of the input structures and substructures. Experimental results performed on sequences and trees generated by a context-free grammar show the effectiveness of the proposed approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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Sperduti, A. (2006). Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_37
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DOI: https://doi.org/10.1007/11840817_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38625-4
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