Call for Papers

Scope of the Conference:

  • statistical learning
  • neural network learning
  • learning through fuzzy logic
  • learning through evolution (evolutionary algorithms)
  • reinforcement learning
  • multistrategy learning
  • cooperative learning
  • planning and learning
  • multi-agent learning
  • online and incremental learning
  • scalability of learning algorithms
  • inductive learning
  • inductive logic programming
  • Bayesian networks
  • support vector machines
  • case-based reasoning
  • evolutionary computation
  • machine learning and natural language processing
  • multi-lingual knowledge acquisition and representation
  • grammatical inference
  • knowledge discovery in databases
  • knowledge Intensive Learning
  • machine learning and information retrieval
  • machine learning for bioinformatics and computational biology
  • machine learning for web navigation and mining
  • learning through mobile data mining
  • text and multimedia mining through machine learning
  • distributed and parallel learning algorithms and applications
  • feature extraction and classification
  • theories and models for plausible reasoning
  • computational learning theory
  • cognitive modeling
  • hybrid learning algorithms
  • machine learning in:
    • game playing and problem solving
    • intelligent virtual environments
    • industrial and engineering applications
    • homeland security applications
    • medicine, bioinformatics and systems biology
    • economics, business and forecasting applications

Contributions describing applications of machine learning (ML) techniques to real-world problems, interdisciplinary research involving machine learning, experimental and/or theoretical studies yielding new insights into the design of ML systems, and papers describing development of new analytical frameworks that advance practical machine learning methods are especially encouraged.

ICMLA'11