ICMLA 2012 - The eleventh International Conference on Machine Learning and Applications (ICMLA'12)

Website www.icmla-conference.org/icmla12 | Edit Freely

Category ICMLA 2012

Deadline: July 04, 2012 | Date: December 12, 2012-December 15, 2012

Venue/Country: Florida, U.S.A

Updated: 2011-11-23 18:52:26 (GMT+9)

Call For Papers - CFP

ICMLA'12

The aim of the conference is to bring researchers working in the areas of machine learning and applications together. The conference will cover both theoretical and experimental research results. Submission of machine learning papers describing machine learning applications in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, game playing and problem solving is strongly encouraged.

The conference proceedings will be published by IEEE.

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.