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MLAMDA 2023 : 2023 Asia Conference on Machine Learning, Algorithms, Modeling and Data Analysis (MLAMDA 2023) | |||||||||||||||
Link: http://www.mlamda.net/ | |||||||||||||||
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Call For Papers | |||||||||||||||
2023 Asia Conference on Machine Learning, Algorithms, Modeling and Data Analysis (MLAMDA 2023)
Website: http://www.mlamda.net/ Venue: Xiamen, China (both online and in-person) Conference Date: December 8-10, 2023 2023 Asia Conference on Machine Learning, Algorithms, Modeling and Data Analysis (MLAMDA 2023) will be held in Xiamen, China during December 8-10, 2023. It is sponsored by The International Society for Applied Computing (ISAC) and The Technical Institute for Engineers (T.I.E.). During the upcoming conference, the invited renowned professors will share with us the recent innovations in the fields of Machine Learning, Algorithms, Modeling and Data Analysis. The conference will mainly feature on keynote speeches as well as peer-reviewed paper presentations. In addition, social program or academic visit will be arranged to encourage communication, discussion or cooperation among the researchers in this field. We invite submissions of papers presenting an original high-quality research and development for the conference. All papers must be written in English and will be peer-reviewed by technical committees of the Conference and all accepted papers will be published in the conference proceedings. *Conference Speakers: Keynote Speaker I: Prof. Dapeng Oliver Wu, City University of Hong Kong, China Keynote Speaker II: Prof. Xiangjie Kong, Zhejiang University of Technology, China (IEEE Senior Member) Keynote Speaker III: Prof. Bekim Fetaji, Mother Teresa University (MTU) – Skopje, North Macedonia Keynote Speaker IV: Prof. Kannimuthu Subramaniyam, Karpagam College of Engineering, India *Call for papers: Deep and Reinforcement Learning Analysis of algorithms Agent Based Simulation Learning for streaming data Machine Learning for Network Slicing Optimization Ant colony algorithm Analytical and Stochastic Modeling Techniques and Applications Learning for structured and relational data Machine Learning for 5G system Approximation algorithm Bond Graph Modeling Mining multi-source and mixed-source information Machine Learning for User Behavior Prediction Combinatorial search Chaos Modeling, Control and Signal Transmission Mixed-type and structure data analytics New Innovative Machine Learning Methods (for more topics: http://www.mlamda.net/Call%20for%20Papers.html) *Publication and indexing: ★All accepted papers will be published in MLAMDA 2023 conference proceedings, which will be submitted for indexing by Ei Compendex and Scopus. *Submission Methods: 1. Online Submission System: https://cmt3.research.microsoft.com/MLAMDA2023 2. Submission Email: mlamda@applied-computing.net Submission guidelines: http://www.mlamda.net/Submission%20Guidelines.html *Join the conference as: Authors: Authors are expected to submit full papers to the submission system for further review by our Technical Committees. All accepted papers after proper registration and presentation in the conference will be published and submitted for indexing. Presenters Only: The presenters are expected to submit abstracts only for presentation in the conference without paper publication in the conference proceedings. Listeners: Listeners are expected to attend the conference without paper presentation or publication. Reviewers: PhD-holders in the research fields of Machine Learning, Algorithms, Modeling and Data Analysis are welcome to be our reviewers and a certificate can be issued. Sponsors/Partners: If you are interested in cooperating with us, such as sponsoring or being a partner of MLAMDA 2023, you are welcome to contact us at: mlamda@applied-computing.net *Contact us: Website: http://www.mlamda.net/ Conference Secretary: Ms. Grace Lee Tel: (+852) 6359 2147 Email: mlamda@applied-computing.net If you have any question or request about our conference, no matter regarding submission, registration, participation or any further question, please send email to us and you will get feedback within 24 hours. |
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