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General Information

Last modified 2007-12-16 09:46

    The 2008 International Conference on Machine Learning; Models, Technologies and Applications (MLMTA'08) is held simultaneously (ie, same location and dates: July 14-17, 2008, Las Vegas, USA) with a number of other joint conferences as part of WORLDCOMP'08 (The 2008 World Congress in Computer Science, Computer Engineering, and Applied Computing). WORLDCOMP'08 is the largest annual gathering of researchers in computer science, computer engineering and applied computing. Many of the joint conferences in WORLDCOMP are the premier conferences for presentation of advances in their respective fields (for the complete list of joint conferences Click Here).

    The motivation is to assemble a spectrum of affiliated research conferences into a coordinated research meeting held in a common place at a common time. The main goal is to provide a forum for exchange of ideas in a number of research areas that interact. The model used to form these annual conferences facilitates communication among researchers in different fields of computer science, computer engineering and applied computing. Both inward research (core areas of computer science and engineering) and outward research (multi-disciplinary, Inter-disciplinary, and applications) will be covered during the conferences.

    The last set of conferences had research contributions from 82 countries and had attracted over 1,850 participants. It is anticipated to have over 2,500 participants for the 2008 event.

    The event will be composed of research presentations, keynote lectures, invited presentations, tutorials, panel discussions, and poster presentations.

    You are invited to submit a draft paper of about 5-7 pages and/or a proposal to organize a Technical Session/workshop (see the Submission information). All accepted papers will be published in the respective conference proceedings. The names of technical session/workshop organizers/chairs will appear on the cover of the proceedings/books as Associate Editors.

    Topics of interest include, but are not limited to, the following:

      General Machine Learning Theory
        • Statistical learning theory
        • Unsupervised and Supervised Learning
        • Multivariate analysis
        • Hierarchical learning models
        • Relational learning models
        • Bayesian methods
        • Meta learning
        • Stochastic optimization
        • Simulated annealing
        • Heuristic optimization techniques
        • Neural networks
        • Reinforcement learning
        • Multi-criteria reinforcement learning
        • General Learning models
        • Multiple hypothesis testing
        • Decision making
        • Markov chain Monte Carlo (MCMC) methods
        • Non-parametric methods
        • Graphical models
        • Gaussian graphical models
        • Bayesian networks
        • Particle filter
        • Cross-Entropy method
        • Ant colony optimization
        • Time series prediction
        • Fuzzy logic and learning
        • Inductive learning and applications
        • Grammatical inference
      General Graph-based Machine Learning Techniques
        • Graph kernel and graph distance methods
        • Graph-based semi-supervised learning
        • Graph clustering
        • Graph learning based on graph transformations
        • Graph learning based on graph grammars
        • Graph learning based on graph matching
        • General theoretical aspects of graph learning
        • Statistical modeling of graphs
Important Date
July 14-17, 2008
The WORLDCOMP'08
25 joint conferences

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Contact: Kaveh Arbtan
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