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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.
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