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CALL FOR PAPERS
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Information Theory and Statistical Learning (ITSL)
Harnessing information processing in biological systems
International conference in conjunction with WORLDCOMP'08
Las Vegas, Nevada (July 14-15, 2008)
http://www.bio-complexity.com/ITSL/ITSL_index.html
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The conference 'Information Theory and Statistical Learning' (ITSL) will
be held as part of WORLDCOMP'08, the 2008 World Congress in Computer
Science, Computer Engineering, and Applied Computing in Las Vegas, Nevada
(USA).
'Information Theory and Statistical Learning' is an interdisciplinary
conference aiming to bring together researches from Information Theory,
Machine Learning, Mathematics, Computational Biology, Biostatistics,
Computer Science, Physics and related areas to present the newest
developments in the interface between Information Theory and Statistical
Learning. Especially, new methods designed for analyzing information
processing in biological systems, e.g., from molecular and cell biology,
genetics or neuroscience, are of central importance.
Another major topic of 'Information Theory and Statistical Learning' is
the application of Information Theory for the analysis of Networks as can
be found nowadays omnipresently in biological, technical, sociological or
economical systems. Furthermore, all aspects of classical Information
Theory topics like compression or coding - applied or theoretical - are
also of interest for ITSL.
TOPICS OF INTEREST include, but are not limited to:
o Classical Aspects of Information Theory
o Information Theory and Statistics
o Data Compression
o Information Theory in Machine Learning
o Coding theory
o Pattern Recognition and Learning
o Signal Processing
o Probabilistic Methods for the Analysis of Algorithms
o MCMC Methods
o Information Geometry
o Information-theoretic Techniques in Discrete Geometry
o Quantum Information Theory
o Information-theoretic Methods for Web/Text Mining
o Information Processing in Complex Networks
# Information-theoretic Methods for Analyzing
Biological Networks
# Information-theoretic Measures to Analyze and
Characterize Network Classes
# Graph Entropy
# Methods in Analytical Combinatorics for Analyzing
Networks
# Measuring Structural Information Content of Networks
# Complexity of Network Structures
# Network Inference based on Information-theoretic
Methods
# Information Theory in Molecular Biology
# Information Theory in Neuroscience
# Probabilistic Methods in Graph Theory
# Network Coding
# Phase Transitions
# Random Networks
# Information-theoretic Methods in Mathematical
Chemistry
IMPORTANT DATES
* March 23, 2008: Submission of papers (about 4 to 6 pages)
* April 17, 2008: Notification of acceptance
* May 3, 2008: Camera-Ready papers and Registration due
* July 14-15, 2008: Conference: Information Theory and Statistical
Learning (ITSL'08)
CONFERENCE CHAIRS
Matthias Dehmer
Michael Drmota
Frank Emmert-Streib
For more information visit the conference website
http://www.bio-complexity.com/ITSL/ITSL_index.html
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