International Conference on Distributed Computing in Sensor
Systems (DCOSS 2021)
June 7 - 9, 2021 | This is going to be a
In the last decade, Machine Learning (ML) and Artificial Intelligence (AI) have emerged as key enablers of advanced wireless networking systems. ML and AI-based techniques are envisioned to help wireless networks meet challenging objectives in terms of high throughput, low delay, and ubiquitous coverage, all with an increasing number of diverse users, and prospectively including human-to-machine or machine-to-machine communications.
The goal of this workshop is to provide a unique platform for researchers and practitioners interested in developing new AI/ML-based techniques to address current and emerging challenges in the design and optimization of traditional and emerging wireless networks. The workshop solicits proposals for novel techniques and methods that integrate basic wireless communication and networking models into ML algorithms to improve the performance of wireless networks and their design and integrability.
We are interested in novel ML/AI theories, models, and algorithms for smart wireless systems including, but not limited to, research on the following topics:
Authors are invited to submit original unpublished manuscripts that demonstrate current research related to ML-SWiN topics of interest. The limit is 8 pages double column single spacing. Please use the US letter size (8.5 X 11 in) standard IEEE conference LaTeX format or Microsoft Word template available here.Note that ML-SWiN does not follow the double-blind review policy. The names and affiliations of all the authors must be present in the submitted manuscript.
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