Workshop on Machine Learning in Wireless Communications (WMLC)
October 21-24, 2024, Seoul, South Korea
Welcome to the Fifth Workshop on the Machine Learning in Wireless Communication Networks, to be held on October in conjunction with WiOpt 2024. The goal of this workshop is to provide a platform for researchers to exchange knowledge and insights on the application of machine learning in the field of wireless communications. We aim to explore the latest trends, challenges, and opportunities in using machine learning techniques for the design, analysis, and optimization of wireless systems (A particularly interesting topic is the possibility of leveraging large models, such as those used in devising ChatGPT, to enhance wireless communications). The scope of the workshop covers various aspects of machine learning and wireless communications, including but not limited to:
- Machine learning for wireless signal processing
- Machine learning for interference management
- Machine learning for resource allocation
- Machine learning for energy efficiency and system sustainability
- Fairness issues in wirelessly networked machine learning systems
- Data and system heterogeneity in machine learning systems
- Communication compression tech in networked machine learning systems
- Operational challenges in networked machine learning systems
- Timeliness-aware distributed algorithms for networked machine learning systems
- Fundamental limits of network parameters on the performance of machine learning systems
- Robust and Private federated reinforcement/meta/deep learning and other novel learning paradigms
- Novel methods for machine learning with limited communication resources
The workshop encourages the submission of original research papers as well as invited papers. The expected audience includes researchers, engineers, and practitioners from academia, industry, and government agencies, who are interested in exploring the potential of machine learning in advancing the state-of-the-art in wireless communications. The workshop will feature keynote talks, technical sessions, and panel discussions, providing ample opportunities for participants to exchange ideas and interact with each other.
Important Dates
- Paper Registration and Submission: September 13, 2024 (23:59 AoE)
- Notification of Acceptance: September 15, 2024 (23:59 AoE)
- Camera Ready and Registration: September 18, 2024 (23:59 AoE)
Submission Guidelines
Information to authors: https://wiopt24.github.io/cfp.html
The submitted and published versions of papers are limited to eight (8) pages in the standard IEEE conference format. Submitted papers should be of sufficient detail to be evaluated by expert reviewers in the field. If full proofs cannot be accommodated due to space limitations, authors are encouraged to cite a publicly accessible long version of the submission that may be considered in the review.
The papers should be submitted via EDAS, and the link will be posted soon.
The submitted and published versions of papers are limited to eight (8) pages in the standard IEEE conference format. Submitted papers should be of sufficient detail to be evaluated by expert reviewers in the field. If full proofs cannot be accommodated due to space limitations, authors are encouraged to cite a publicly accessible long version of the submission that may be considered in the review.
The papers should be submitted via EDAS, and the link will be posted soon.
Workshop Organizers
- Howard H. Yang, ZJU-UIUC Institute, Zhejiang University, China
- Nikolaos Pappas, Department of Computer and Information Science, Linköping University, Sweden
Paper Submission Link
The papers should be submitted via EDAS.
The submission link is https://edas.info/newPaper.php?c=32278&track=126058
The submission link is https://edas.info/newPaper.php?c=32278&track=126058
Schedule
Time: 13:30 - 15:00, October 21, 2024
Location: B119
Session chair: Loannis Pitsiorlas
13:30 - 13:50:
Location: B119
Session chair: Loannis Pitsiorlas
13:30 - 13:50:
- Trustworthy Intrusion Detection: Confidence Estimation Using Latent Space
13:50 - 14:10:
- Meta-Leaning Deep Reinforcement Learning for Fresh Data Collection in UAV-Assisted Wireless Sensor Networks
14:10 - 14:30:
- Reconfigurable Intelligent Surfaces-Assisted Task-Oriented Communications for AI-Driven Vertical Applications
14:30 - 14:50:
- Reducing Latency in NOMA-aided MEC Networks: A Deep Reinforcement Learning Approach
14:50 - 15:10:
- Harmonizing Efficiency and Precision in Semantic-Bit Coexisting Communication Systems
