Special Issue "From Edge Devices to Cloud Computing and Datacenters: Emerging Machine Learning Applications, Algorithms, and Optimizations"

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: 31 October 2022 | Viewed by 154

Special Issue Editor

Prof. Dr. Freddy Gabbay
E-Mail Website
Guest Editor
Faculty of Engineering, Ruppin Academic Center, Emek Hefer 4025000, Israel
Interests: artificial intelligence; machine learning and deep neural network algorithms; deep compression of machine learning; explainable AI (XAI); high performance computing algorithms and acceleration; computation systems and algorithm modeling and simulations
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Special Issue Information

Dear Colleagues,

In the last decade, machine learning has emerged as an important tool for a tremendous number of applications, such as computer vision, medicine, fintech, autonomous systems, speech recognition, and many others. Machine learning models offer state-of-the-art accuracy and robustness in many applications. The increasing deployment of machine learning algorithms from edge and IoT devices to high-end computational infrastructures, such as supercomputers, the cloud, and datacenters, introduces major computational challenges due to the growing amount of data and also the major growth in their model size and complexity. This Special Issue looks for novel developments of emerging machine learning applications, algorithms, and optimization in diverse computational platforms such as:

  • Novel IoT and edge devices’ machine learning applications;
  • High-performance computing machine learning algorithms;
  • Machine learning applications in cloud and fog computing;
  • Fusion of machine learning models between edge and cloud;
  • Machine learning optimization methods such as pruning and deep compression.

Prof. Dr. Freddy Gabbay
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • deep neural network
  • deep compression
  • machine learning optimizations
  • machine learning under constrained resources

Published Papers

This special issue is now open for submission.
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