Recent developments in artificial intelligence (AI) and machine learning, especially in deep learning, has stimulated growing interests to incorporate AI and machine learning into communication systems and networks. While some researchers have advocated applying deep learning tools to communication system (especially receivers) design, others are doubtful as to how much benefits these tools can offer. On one hand, communication systems have been designed and optimized by generations of dedicated efforts for bandwidth, power, and complexity efficiency, and reliability, leaving little room for improvements in most cases. On the other hand, deep learning enabled networks, supported by results such as universal approximation theorem, seem to promise a new and simple design regime where near optimal performance can be achieved by merely using certain ready to use deep learning modules, applying them to communication design problems, and tuning them based on the easily generated training data. The deep learning based approach may offer some new design approaches for traditionally difficult signal processing tasks in communications and networks.
This conference is meant to stimulate the debate and provide a forum for researchers working in related problems to exchange ideas and recent results (both positive and negative ones) in applying artificial intelligence to communications and networks. Both supervised learning and unsupervised learning, reinforcement learning, and recent developments in generative adversarial networks, and game-theoretic setups are also of great interests.
Welcome to the EAI Community
Let the EAI Community help you build your career with collaborative research, objective evaluation, and fair recognition:
- Get more visibility for your paper and receive a fair review with Community Review,
- Earn credits regardless of your paper’s acceptance and increase your EAI Index for new membership ranks and global recognition,
- Find out if your research resonates – get real-time evaluation of your presentation on-site via EAI’s Mobile Compass.
The topics will include, but are not limited to the following:
- Deep Learning/Machine Learning on Information and Signal Processing
- AI in Ubiquitous Mobile Wireless Communications
- AI-based Network Transmission and Traffic Scheduling
- AI for Security in Communication Networks
- AI-based Network Intelligence for IoT
- Recent Advances in AI theory and its applications
All registered papers will be published by Springer and made available through SpringerLink Digital Library.
Proceedings will be submitted for inclusion in leading indexing services, Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).
Authors of selected papers will be invited to submit an extended version to:
Additional publication opportunities:
- EAI Transactions series (Open Access)
- EAI/Springer Innovations in Communications and Computing Book Series
Community Review is a service offered to Program Committees and submitting Authors of all EAI conferences designed to improve the speed and the quality of the review process.
Abstracts of all authors who opt in to Community Review during submission will be published and available for Bidding here.
Papers should be from 6 to 12 pages long with reference.