Connectionists: Special Session on "ADVANCED NEURAL PROCESSING SYSTEMS" at KES2008

[Franco Scarselli]

** Our apologies if you receive multiple copies of this announcement **


	Special Session "ADVANCED NEURAL PROCESSING SYSTEMS"
      		12th International Conference on
  Knowledge-Based and Intelligent Information & Engineering Systems
  			 Zagreb, Croatia
		   3, 4 and 5 September 2008


Call for papers
The research in the neural network field has come to its maturity, both
from the theoretical and the practical point of view. Nevertheless, some
problems still remain unsolved, since classical connectionist models seem
unable to cope with difficult applications, involving complex data. Recent
studies on statistical pattern recognition and neural networks show
possible directions to exploit structural information in problems which
are inherently of topological nature. On the other hand, the actual trend
for facing difficult applications is that of using hybrid approaches,
integrating in a unique framework neural networks, kernel machines, and
statistical techniques. This new scenario imposes studying new models, new
learning algorithms, and assessing their properties both theoretically and
experimentally.

The scope of this session is, but not limited to:
- Algorithms and Architectures: statistical learning algorithms, neural
  networks, kernel methods, dimensionality reduction and manifold
  learning, model selection.
- Applications: innovative applications that use machine learning,
  including systems for time series prediction, bioinformatics, text/web
  analysis, multimedia processing, and robotics.
- Cognitive Science and Artificial Intelligence: theoretical, computational,
  or experimental studies of perception, reasoning, problem solving, and
  natural language processing.
- Control and Reinforcement Learning: planning, navigation, Markov decision
  processes, game-playing.
- Learning Theory: generalization, regularization and model selection, new
  learning paradigms, spaces of functions and kernels, online learning and
  competitive analysis, hardness of learning and approximations, information
  theory.
- Learning in Graphical Domains: neural network models for graphs, SVMs and
  kernel methods for graphs, probabilistic models for graphs, statistical
  relational learning, and pattern recognition applications involving
  graphical data.


Paper submission
Authors are encouraged to submit high quality, original work that has neither appeared in, nor is under consideration by, other conferences/journals. All submissions will be refereed by experts in the field based on originality, significance, and clarity. The conference preceedings will be published by Springer-Verlag in Lecture Notes in AI as part of the LNCS/LNAI series. When formatting papers - that must be no more than eight (8) pages long, including figures and bibliography - please refer to the Springer-Verlag site and strictly follow the instructions for LNCS authors (http://www.springer.de/comp/lncs/authors.html).

Important Dates
.	Deadline for paper submission: March 10th 2008
.	Notification of acceptance: April 10th 2008
.	Camera-ready papers: May 1st 2008

Organized by:
Chairs
.       Monica Bianchini, Marco Maggini, Franco Scarselli
        University of Siena, Italy

Program Committee (To be completed)
.	Simone Fiori, Politechnic University of Marche, Italy
.	Barbara Hammer, Clausthal University of Technology, Germany
.       Alfredo Petrosino, University of Naples "Parthenope", Italy
.	Friedhelm Schwenker, University of Ulm, Germany
.	Peter Tino, The University of Birmingham, United Kingdom
.       Edmondo Trentin, University of Siena, Italy

Other details are available at:
http://www.dii.unisi.it/~monica/KES2008_SSANPS/index.html