ANN: Special issue on connectionist models for learning in structured domains

From: Paolo Frasconi (paolo@dsi.unifi.it)
Date: Wed May 02 2001 - 16:55:07 MET DST

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    The members of this list may be interested in the most recent issue of
    the IEEE Transactions on Knowledge and Data Engineering which is a
    Special Issue on Connectionist Models for Learning in Structured
    Domains.

      IEEE Transactions on Knowledge and Data Engineering
         Vol. 13, No. 2, March/April 2001

          SPECIAL SECTION ON CONNECTIONIST MODELS FOR
          LEARNING IN STRUCTURED DOMAINS

    Abstracts can be found at http://www.dsi.unifi.it/neural/tkde-datas.html

    Full text is available to subscribers from the IEEE TKDE home page
    http://computer.org/tkde/index.htm

    Guest Editorial Introduction to the Special Section
    P. Frasconi, M. Gori, and A. Sperduti

    Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural
    Networks
    R.C. Carrasco and M.L. Forcada

    Integrating Linguistic Primitives in Learning Context-Dependent
    Representation
    S.W.K. Chan

    Symbolic vs. Connectionist Learning: An Experimental Comparison in a
    Structured Domain
    P. Foggia, R. Genna, and M. Vento

    Generalization Ability of Folding Networks
    B. Hammer

    Hierarchical Growing Cell Structures: TreeGCS
    V.J. Hodge and J. Austin

    Incremental Syntactic Parsing of Natural Language Corpora with Simple
    Synchrony Networks
    P.C.R. Lane and J.B. Henderson

    Learning Distributed Representations of Concepts Using Linear
    Relational Embedding
    A. Paccanaro and G.E. Hinton

    Clustering and Classification in Structured Data Domains Using Fuzzy
    Lattice Neurocomputing (FLN)
    V. Petridis and V.G. Kaburlasos

    Representation and Processing of Structures with Binary Sparse
    Distributed Codes
    D.A. Rachkovskij

    [Sorry, I can provide no hardcopies - for electronic copies, please
    contact the authors directly].

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