Applications Based on Symmetry/Asymmetry in Machine Learning
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 May 2024 | Viewed by 327
Special Issue Editors
Interests: cloud; fog and edge computing; internet of things; network security; data privacy; ad-hoc and wireless sensor networks; data modelling
Interests: social networks analysis; complex networks; distributed systems
Special Issue Information
Dear Colleagues,
This Special Issue aims to explore the applications of symmetry and asymmetry in machine learning with a focus on supporting blockchain technology. Symmetry and asymmetry play crucial roles in various aspects of machine learning, including data representation, feature extraction, classification, and anomaly detection. This Special Issue invites authors to contribute their research on the innovative utilization of symmetry and asymmetry in machine learning algorithms and techniques for blockchain applications. The goal is to deepen our understanding of how symmetry and asymmetry can enhance the efficiency, security, and scalability of blockchain systems while leveraging the potential of machine learning.
Dr. Masoud Barati
Dr. Ahmad Zareie
Dr. Vahid Seydi
Guest Editors
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. Symmetry is an international peer-reviewed open access monthly 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 2400 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
- federated learning
- blockchain technology
- data representation and modelling
- data classification
- anomaly detection
- security
