ICMLA: International Conference on Machine Learning and Applications



Past:   Proceedings on DBLP

Future:  Post a CFP for 2020 or later   |   Invite the Organizers Email


All CFPs on WikiCFP

Event When Where Deadline
ICMLA 2019 18th IEEE International Conference on Machine Learning and Applications
Dec 16, 2019 - Dec 19, 2019 Boca Raton, Florida, USA Sep 7, 2019
ICMLA 2017 16th IEEE International Conference On Machine Learning And Applications
Dec 18, 2017 - Dec 21, 2017 CANCUN, MEXICO Jul 6, 2017
ICMLA 2016 IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16)
Dec 18, 2016 - Dec 20, 2016 Los Angeles, California, USA Jul 6, 2016
ICMLA 2013 IEEE International Conference on Machine Learning and Applications
Dec 4, 2013 - Dec 7, 2013 Miami, Florida, USA Jul 22, 2013
ICMLA 2012 Eleventh International Conference on Machine Learning and Applications
Dec 12, 2012 - Dec 15, 2012 Boca Raton, USA Jul 20, 2012
ICMLA 2011 Tenth International Conference on Machine Learning and Applications
Dec 18, 2011 - Dec 21, 2011 Honolulu, USA Jul 25, 2011
ICMLA 2010 International Conference on Machine Learning and Applications
Dec 11, 2010 - Dec 13, 2010 Fairfax, USA Jul 6, 2010
ICMLA 2009 The Eighth Interational Conference on Machine Learning and Applications
Dec 13, 2009 - Dec 15, 2009 Miami, FL, USA Jul 6, 2009
ICMLA 2008 International Conference on Machine Learning and Applications
Dec 11, 2008 - Dec 13, 2008 San Diego, CA, USA Jun 15, 2008
ICMLA 2007 International Conference on Machine Learning and Applications
Dec 13, 2007 - Dec 15, 2007 Cincinnati, OH Oct 1, 2007 (Jun 15, 2007)

Present CFP : 2019

ICMLA 2019 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 machine learning, 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. 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.

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.

The technical program will consist of, but is not limited to, the following topics of interest:

statistical learning
neural network learning
learning through fuzzy logic
learning through evolution (evolutionary algorithms)
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
machine learning for bioinformatics and computational biology
multi-lingual knowledge acquisition and representation
grammatical inference
knowledge acquisition and learning
knowledge discovery in databases
knowledge intensive learning
knowledge representation and reasoning
machine learning and information retrieval
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

Applications of machine learning in:

medicine, health, bioinformatics and systems biology
industrial and engineering applications
security applications
smart cities
game playing and problem solving
intelligent virtual environments
economics, business and forecasting applications, etc.

The conference will include a number of interesting keynote plenary talks, which will be announced on the conference web site as arrangements are finalized. Previous invited speakers included numerous fellows of IEEE, AMIA, AAAS, AAAI, etc.

Paper Submission

High quality papers in all Machine Learning areas are solicited. Papers that present new directions in ML will receive careful reviews. Authors are expected to ensure that their final manuscripts are original and are not appearing in other publications. Paper should be limited to 8 pages and submitted in IEEE format (double column). Papers will be reviewed by the Program Committee on the basis of technical quality, originality, significance and clarity. All submissions will be handled electronically. Accepted papers will be published in the conference proceedings, as a hardcopy. Authors of the accepted papers need to present their papers at the conference. A selected number of accepted papers will be invited for possible inclusion, in an expanded and revised form, in some journal special issues.

ICMLA'19 Best Paper Award and ICMLA'19 Best Poster Award will be conferred at the conference to the authors of the best research paper and best poster presentation, respectively, based on the reviewers and Programme Committee recommendations.

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