Call for Book Chapters

Chapter proposal submission deadline: June 15, 2008

Full chapter deadline: July  30,  2008

There is no apriori limit on the number of pages, in principle, 30 pages is a reasonable limit.


                

 

Learning and Approximation: Theoretical Foundations and Applications

 

Volume (s) Editors: Ajith Abraham, Aboul-Ella Hassanien, and Athanasios Vasilakos

To be published in "Studies in Computational Intelligence" published by Springer Verlag, Germany


                                                                     Book Aim and Objective

     Approximation and Learning  algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes,  coloring and partitioning, competitive analysis, computational finance, cuts and connectivity,  geometric problems, inapproximability results,  mechanism design,  network design,  packing and covering,  paradigms for design and analysis of approximation and online algorithms,  randomization techniques,  real-world applications, and  scheduling problems. The past years have witnessed a large number of interesting applications of various computational intelligence techniques, such as rough sets, Neural Networks; Fuzzy Logic; Evolutionary Computing; Artificial Immune Systems; Swarm Intelligence; Reinforcement Learning and evolutionary computation, to intelligent multimedia processing.  In spite of numerous successful applications of computational intelligence techniques in business and industry, it is sometimes difficult to explain from a theoretical perspective. Therefore, we encourage authors to present original chapter dealing with the incorporation of such CI techniques into  Learning and Approximation algorithms  and processes. 


Topics

 

 

Topics include, but are not limited to:

  • Statistical learning algorithms,
  • Theoretical foundations of learning in large probabilistic environments.
  • Neural networks,
  •  kernel methods,
  • Graphical models,
  • Gaussian processes,
  • Learning in complex systems. Function approximation, dimensionality reduction, feature selection for learning, and alternative state representations.
  • Cooperative and competitive multi-agent reinforcement learning. Learning in nonstationary domains and stochastic, network, and dynamic games.
  • Dimensionality reduction and manifold learning,
  •  Reinforcement Learning with Approximation Spaces
  • Model selection,
  • Combinatorial optimization,
  • Relational learning.
  • Neuroimaging,
  • Cognitive neuroscience,
  • EEG (electroencephalogram),
  • ERP (event related potentials),
  • MEG (magnetoencephalogram),
  • fMRI (functional magnetic resonance imaging),
  • Brain mapping, brain segmentation, and brain computer interfaces.
  • Cognitive Science and Artificial Intelligence: theoretical, computational, or experimental studies of perception, psychophysics, human or animal learning,  reasoning, problem solving, natural language processing, and neuropsychology.
  • Control and Reinforcement Learning
  • Learning Theory: generalization, regularization and model selection, Bayesian learning, spaces of functions and kernels, statistical physics of learning, online learning and competitive analysis, hardness of learning and approximations, large deviations and asymptotic analysis, information theory.
  • Neuroscience: theoretical and experimental studies of processing and transmission of information in biological neurons and networks, including spike train generation, synaptic modulation, plasticity and adaptation.
  • Innovative applications  that use machine learning, including systems for time series prediction, bioinformatics, text/web analysis, multimedia processing, and robotics.
  • Etc.

 


  Submission Guidelines and important dates

         Researchers and practitioners are kindly invited to send on or before June 15  2008 a short email to

 

Aboitcairo@gmail.com

 

containing a preliminary title and a short abstract of their chapter. This will facilitate the planning of the review process.  All chapter proposals will be peer reviewed.  Full chapters will be expected by July 30  2008. All submitted chapters will be reviewed by at least three reviewers on a double-blind review basis.  

 

June 15   2008

Deadline for chapter proposals ( title and short abstract)

July  30  2008

Deadline for full chapters

September 30, 2008

Notification of acceptance/rejection of chapters

October 15  2008

Deadline for submission of final chapters


 Original artwork and a signed copyright release forms will be required for all accepted chapters.




Volume Editors

 

 

Ajith Abraham

 

Center for Quantifiable Quality of Service in Communication Systems 
Norwegian University of Science and Technology,

 O.S. Bragstads plass 2E, N-7491 Trondheim, Norway
Email: ajith.abraham@ieee.org abraham.ajith@acm.org 

URL: http://www.softcomputing.net

 Aboul-Ella Hassanien

 

Kuwait University

College of Business Administration,

Quantitative Methods and IS Department

P.O. Box 5486 Safat, 13055 Kuwait

Tel: 965-4839364

Email: Abo@cba.edu.kw

URL:  http://www.cba.edu.kw/abo

Athanasios Vasilakos
Dept. of Computer and Telecommunications Engineering
University of Western Macedonia
vasilako@ath.forthnet.gr
http://www.hindawi.com/81797846.html

 


About the series "Studies in Computational Intelligence"

 

 

 

 

 

      The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.


Instructions for Authors (Preparation of Manuscripts)

   Careful preparation of the manuscripts will help keep production time short and ensure satisfactory appearance of the finished book. Please prepare the manuscript using the author guidelines and format given in the following link:

http://www.softcomputing.net/cec06/author-kit.zip


Contact information

 

Aboul-Ella Hassanien (Abo )

 Kuwait University
College of Business Administration
Quantitative and Information System Department
P.O. Box 5486 Safat
Code No. 13055
Kuwait
E-mail:
Aboitcairo@gmail.com

http://www.cba.edu.kw/abo