ICMLA: International Conference on Machine Learning and Applications

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2022 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
ICMLA 2021 20th IEEE International Conference on Machine Learning and Applications
Dec 13, 2021 - Dec 16, 2021 Pasadena, California, USA Jul 3, 2021
ICMLA 2020 International Conference on Machine Learning and Applications
Dec 16, 2020 - Dec 19, 2020 Copenhagen, Denmark TBD
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 : 2021

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.

Scope of the Conference:

•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

•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 modelling

•adversarial learning

•machine leaning privacy

•hybrid learning algorithms

•deep learning

•big data

•machine learning in:

o game playing and problem solving
o intelligent virtual environments
o industrial and engineering applications
o homeland security applications
o medicine, bioinformatics and systems biology
o 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.


Paper Submission Formats:

Papers submitted for reviewing should conform to IEEE specifications. Manuscript templates can be downloaded from IEEE website (http://www.ieee.org/conferences_events/conferences/publishing/templates.html) but without information about authors to conform with double-blind policy. The maximum length of papers is 8 pages.


Submission:

Please follow the link (https://cmt3.research.microsoft.com/ICMLA2021/) for initial submission and updates.
 

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