CFP: Special Issue on Learning in Structured Domains

[Paolo Frasconi]

CALL FOR PAPERS

Special issue on Connectionist Models for Learning in Structured Domains
IEEE Transactions on Knowledge and Data Engineering
          
Submission deadline: July 30, 1999


BACKGROUND

Structured representations  are   ubiquitous  in  different fields  such    as
knowledge representation, language modeling, and pattern recognition. Although
many of  the  most successful connectionist  models  are  designed for  "flat"
(vector-based)  or    sequential  representations,    recursive    or   nested
representations should be preferred in several situations. One obvious setting
is concept  learning when objects  in the instance space are  graphs or can be
conveniently represented as graphs.  Terms  in first-order logic,  blocks   in
document processing, patterns in structural and  syntactic pattern recognition,
chemical compounds,   proteins in molecular biology,  and  even world wide web
sites, are all entities which are best represented as graphical structures, and
they cannot be easily dealt with  vector-based  architectures.  In other cases
(e.g.,  language processing)  the  process  underlying  data  has a   (hidden)
recursive  nature but only a  flat representation is   left as an observation.
Still, the architecture should be able  to deal with recursive representations
in order to model correctly the mechanism that generated the observations.

The interest in developing connectionist architectures capable of dealing with
these rich representations can  be traced back to the  end of the  80's. Early
approaches include Touretzky's BoltzCONS,  the Pollack's RAAM  model, Hinton's
recursive distributed representations.  More recent techniques include labeled
RAAMs,    holographic  reduced     representations,   and   recursive   neural
networks. Today, after more than ten years since  the explosion of interest in
connectionism,  research  in   architectures    and algorithms for    learning
structured  representations still  has  a  lot  to  explore and no  definitive
answers have  emerged. It seems that  the  major difficulty with connectionist
models is not just  representing symbols, but rather  devising proper ways  of
learning when examples  are data structures, i.e.  labeled graphs  that can be
used  for   describing  relationships  among  symbols  (or,   more in general,
combinations of symbols and continuously-valued attributes).


TOPICS

The aim of this special issue  is to solicit  and publish valuable papers that
bring  a clear picture of the  state of the   art in this  area.  We encourage
submissions of  papers addressing, in addition to  other  relevant issues, the
following topics:

 * Algorithms and architectures for classification of data structures.
 * Unsupervised learning in structured domains. 
 * Belief networks for learning structured patterns.
 * Compositional distributed representations. 
 * Recursive autoassociative memories.
 * Learning structured rules and structured rule refinement. 
 * Connectionist learning of syntactic parsing from text corpora.
 * Stochastic grammars and their relationships to neural and belief networks.
 * Links between connectionism and syntactic and structural pattern
   recognition. 
 * Analogical reasoning.
 * Applications, including:
   - Medical and technical diagnosis: discovery and manipulation of structured
     dependencies, constraints, explanations. 
   - Molecular biology and chemistry: prediction of molecular structure
     folding, classification of chemical structures. 
   - Automated reasoning: robust matching, manipulation of logical terms,
     proof plans, search space reduction. 
   - Software engineering: quality testing, modularization of software.
   - Geometrical and spatial reasoning: robotics, structured representation of
     objects in space, figure animation, layouting of objects.  


INSTRUCTIONS

We  encourage  e-mail submissions  (Postscript,  RTF,  and  PDF  are  the only
acceptable formats). For hard  copy  submission please  send  6 copies of  the
manuscript to Prof. Marco Gori.  Manuscripts should not exceed 30 pages double
spaced (excluding Figures and  Tables). The title and  the abstract  should be
sent separately in  ASCII format, even  before  the final submission, so  that
reviewers can be contacted timely.


IMPORTANT DATES

Submission of title and abstract (e-mail): July 15, 1999
Submission deadline: July 30, 1999
Notification of acceptance: December 31, 1999
Expected publication date: Mid-to-late 2000.


GUEST EDITORS

Prof. Paolo Frasconi           
DIEE, University of Cagliari   
Piazza d'Armi 09123 Cagliari (ITALY)
Phone:  +39 070 675 5849
E-mail: paolo at diee.unica.it      

Prof. Marco Gori
DII, University of Siena
Via Roma 56, 53100 Siena (ITALY)
Phone:  +39 0577 263 610
E-mail: marco at ing.unisi.it

Prof. Alessandro Sperduti
DI, University of Pisa
Corso Italia 40, 56125 Pisa (ITALY)
Phone:  +39 050 887 213
E-mail: perso at di.unipi.it