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Subject: 20th IEEE International Conference on Machine Learning and Applications Pasadena, California, Dec. 13-16, 2021
From: SEWORLD Moderator <[log in to unmask]>
Reply-To:SEWORLD Moderator <[log in to unmask]>
Date:Mon, 19 Apr 2021 13:28:00 -0000
Content-Type:text/plain

[Please accept our apologies if you receive multiple copies of this email]


Call for Papers

20th IEEE International Conference on Machine Learning and Applications

Pasadena, California, Dec. 13-16, 2021

http://www.icmla-conference.org/icmla21



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.



*Key Dates:*



PROPOSALS DUE

Special Sessions/Workshops:                        May 10, 2021

Tutorials:                                                        July 6,
2021

PAPER SUBMISSION DEADLINE (All paper submission deadlines are "Anywhere On
Earth." )

            Main Conference:                                           July
3, 2021

Special Sessions/Workshops/Challenges:      August 6, 2021

            Notification of Acceptance:                           September
4, 2021

Camera-ready Papers:                                    October 1, 2021

Pre-registration:                                              October 1,
2021



*Scope of the Conference:*



We encourage submissions of high quality research papers on all topics in
the general area of machine learning and its applications. Topics of
interest include, but are not limited to, the following areas:

   - General Machine Learning (e.g., statistical learning, reinforcement
   learning, supervised learning, unsupervised learning, clustering, hybrid
   learning, federated learning, online and incremental learning, ranking,
   feature selection, few-shot learning, evolutionary learning, etc.)
   - Deep Learning (neural network models, deep reinforcement learning,
    etc.)
   - Learning Theory (game theory, statistical learning theory,
   computational learning theory, plausible reasoning theory and models,
   etc.)
   - Machine Learning performance and optimization (network architectures
   search, pruning, quantization, learning low capacity devices, scalability
   of learning algorithms, system, performance, offloading, distributed and
   parallel learning, etc.)
   - Probabilistic Inference (Bayesian methods, graphical models, Monte
   Carlo methods, etc.)
   - Trustworthy Machine Learning (security, privacy, adversarial learning,
   etc.)
   - Applications (gaming, problem solving, virtual environments, industry,
   manufacturing, homeland security, medicine, bioinformatics and system
   biology, healthcare, neuroscience, economics, business, social good, web,
   mobile data, time series data, multimedia data, natural language
   processing, data mining, information retrieval, knowledge discovery, etc.)

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 with
maximum length of 8 pages. Manuscript templates can be downloaded from IEEE
website (
http://www.ieee.org/conferences_events/conferences/publishing/templates.html).
All submissions must be anonymized and may not contain any information with
the intention or consequence of violating the double-blind reviewing
policy, including (but not limited to) citing previous works of the authors
or sharing links in a way that can infer any author’s identity or
institution, actions that reveal the identities of the authors to potential
reviewers.



*Submission:*

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



*Journal Publication:*

A short list of presented papers will be selected so that revised and
extended versions of these papers will be published in 1) special issue on
Application of Machine Learning Techniques for Sensing and Imaging of
Sensors of MDPI Sensors <https://www.mdpi.com/journal/sensors>; 2) Journal
of Machine Learning Theory, Applications and Practice
<https://www.journal.riverpublishers.com/index.php/JMLTAP/> (JMLTAP) by
River Publishers



*Organizing Committee:*



Conference Co-Chairs:

Ishwar K Sethi, Oakland University

Weisong Shi, Wayne State University



Program Committee Co-Chairs:

Daniela Raicu, DePaul University

Guangzhi Qu, Oakland University



Special Sessions Chair:

Ruoming Jin, Kent State University



Tutorials Chair:

Mahdi Khosravy, Osaka University, Japan



Publicity Chair:

Tegjyot Singh Sethi
-- 
-----------------------------------------------------------------
Guangzhi Qu, Ph.D.
Professor
Computer Science and Engineering Department
Oakland University, Rochester, MI 48309
Tel: (248) 370-2690 Fax: (248) 370-4625
Email: [log in to unmask]
Http://www.secs.oakland.edu/~gqu/
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