Special issue on connectionist models for learning in structured domains

[Paolo Frasconi]

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].