Scope of the Conference

ICMLA 2017 aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML). The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the conference aims to attract researchers and application developers from a wide range of ML related areas, and the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges.

Topics of interest

  • Statistical Learning
  • Neural Network Learning
  • Learning Through Fuzzy Logic
  • Learning Through Evolution
  • Reinforcement Learning
  • Multi-strategy 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
  • Grammatical Inference
  • Knowledge Acquisition and Learning
  • Knowledge Discovery in Databases
  • Knowledge Intensive Learning
  • Knowledge Representation and Reasoning
  • Machine Learning for Information Retrieval
  • Learning Through Mobile Data Mining
  • Machine Learning for Web Navigation and Mining
  • Text and Multimedia Mining
  • Feature Extraction and Classification
  • Distributed and Parallel Learning Algorithms and Applications
  • Computational Learning Theory
  • Theories and Models for Plausible Reasoning
  • Computational Learning Theory
  • Cognitive Modeling
  • Hybrid Learning Algorithms
  • Multi-lingual knowledge acquisition and representation
  • Applications of Machine learning in:
    • Medicine and health informatics
    • Bioinformatics and systems biology
    • Industrial and engineering applications
    • Security
    • Smart cities
    • Game playing and problem solving
    • Intelligent virtual environments
    • Economics, business and forecasting

Applications of Machine Learning

The conference will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged.