Exact solutions for recursive principal components analysis of sequences and trees

  • Authors:
  • Alessandro Sperduti

  • Affiliations:
  • Department of Pure and Applied Mathematics, University of Padova, Italy

  • Venue:
  • ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
  • Year:
  • 2006

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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.