Dear GR Community, This deadline has been extended until Feb 1! Please consider contributing your work to this workshop! Hoping to see GNU Radio making an appearance & impact here! I apologize for the repeated announcement :-) Best, Tim
> On Jan 25, 2020, at 10:20 AM, West, Nathan <n...@ostatemail.okstate.edu> > wrote: > > Hi all, > > Please consider contributing your work or demonstration proposals to the > workshop at IEEE ICC if you are working at the intersection of communications > systems and machine learning. Please see the CFP below for details. > > -Nathan > > Call for Papers: > > IEEE ICC 2020 Open Workshop on Machine Learning in Communications > > 7-11 June 2020, Dublin, Ireland > > ** Submission deadline: January 27, 2020 ** > > https://icc2020.ieee-icc.org/workshop/ws-19-open-workshop-machine-learning-communications/ > > <https://icc2020.ieee-icc.org/workshop/ws-19-open-workshop-machine-learning-communications/> > > =================== > Call For Papers > =================== > Machine Learning in Communications is a rapidly growing field within > networking and communications with the potential to substantially transform > wireless, optical, and other modes of networking and communications > engineering in a wide range of future systems by leveraging measurement, > data, feedback, domain knowledge, and learning to achieve optimality for a > wide range of performance metrics. By directly exploiting real data, > representation learning, end-to-end learning, reinforcement learning, > concurrent neuromorphic processing, and a wide range of concepts which have > advanced rapidly in the machine learning community in recent years, ML-Comms > holds the promise to discover alternative and superior ways for information > processing in practical application scenarios where deficient or inaccurate > models limit present development. ` > Openness and Reproducibility are two essential components in conducting > rigorous machine learning driven research, and this workshop seeks to > highlight and encourage both of these to help further increase the maturity > of communications as a data science. > · Authors are strongly encouraged to utilize open tools such as > pre-publication (e.g. ArXiv), providing reference code, data, simulations, > GNU Radio modules, etc. openly (e.g. Github), and fully describe their > methodologies in an open and re-producible way such that others can easily > validate, leverage and build upon their work. > · For accepted workshop papers meeting such criterion, IEEE ComSoc is willing > to provide as Open-Access publications at no additional fee to the authors! > > MLC Dataset Challenge: In this year’s ICC 2020 Open Workshop, we are also > excited to announce an open-dataset challenge focused on the unique task of > Vision-Aided Beam Tracking for mmWave Systems. This challenge will adopt the > recently developed ViWi dataset. Additional details of the competition and > submission will be provided in early February 2020 via the workshop webpage: > https://icc2020.ieee-icc.org/workshop/ws-19-open-workshop-machine-learning-communications > > <https://icc2020.ieee-icc.org/workshop/ws-19-open-workshop-machine-learning-communications>. > The workshop expects to announce results at the ICC’2020 on a hold-out test > set and invite competitors to share their approaches and experiences. > > We invite submissions of unpublished works on the application and theory of > machine learning to communications. The workshop shall not restrict the type > of machine learning techniques and applications but does provide the > following list is a non-exhaustive list of suggested topics. > · Machine learning driven design and optimization of modulation and coding > schemes > · Machine learning techniques for channel estimation, channel modeling, and > channel prediction. > · Machine learning based enhancements for difficult to model communications > channels such as molecular, biological, multi-scale, and other > non-traditional communications mediums > · Transceiver design and channel decoding using deep learning > · Machine learning driven techniques for radio environment awareness and > decision making > · Machine learning for Internet of things (IoT) and massive connectivity. > · Machine learning for ultra-reliable and low latency communications (URLLC). > · Machine learning for Massive MIMO, active and passive Large Intelligent > Surfaces (LIS). > · Distributed learning approaches for distributed communications problems > · (Deep) Reinforcement Learning and Policy learning for resource management & > optimization > · Reinforcement Learning for self-organized networks and AP/BTS optimization > · Machine learning techniques for non-linear signal processing > · Low-complexity and approximate learning techniques and power reduction > applications > · Machine learning for edge Intelligence, sensing platforms, and sense making > · Algorithmic advances in machine learning for communication systems > · Advancing the joint understanding of information theory, capacity, > complexity and machine learning communications systems > · Machine learning methods for exploiting complex spatial, traffic, channel, > traffic, power and other distributions more effectively using measurement vs > idealized distributions. > · Compression of neural networks for low-complexity hardware implementation > · Unsupervised, semi-supervised and self-supervised learning approaches to > communications > > =================== > Important Dates > =================== > Paper submission deadline: January 27, 2020 > Notification of acceptance: February 20, 202 > Camera-ready papers: March 1, 2020 > =================== > Paper Submission > =================== > The workshop accepts only novel, previously unpublished papers. The page > length limit for all initial submissions for review is SIX (6) printed pages > (10-point font) and must be written in English. Initial submissions longer > than SIX (6) pages will be rejected without review. All final submissions of > accepted papers must be written in English with a maximum paper length of six > (6) printed pages (10-point font) including figures. No more than one (1) > additional printed page (10-point font) may be included in final submissions > and the extra page (the 7th page) will incur an over length page charge of > USD100. For more information, please see IEEE ICC 2020 official website: > https://icc2020.ieee-icc.org/authors/call-workshop-papers > <https://icc2020.ieee-icc.org/authors/call-workshop-papers> > > EDAS submission link: https://edas.info/newPaper.php?c=26827 > <https://edas.info/newPaper.php?c=26827> > Please note we are also accepting submissions for live demonstrations and > prototype systems in the ML-Comms area via abstract as well! Please see the > full CFP pdf on the workshop webpage for additional details! > > =================== > Workshop Organizers > =================== > · Tim O'Shea, DeepSig & Virginia Tech, US > · Elisabeth de Carvalho, Aalborg University, DK > · Jakob Hoydis, Nokia Bell Labs, FR > · Marios Kountouris, EURECOM, FR > · Zhi Ding, UC Davis, US > =================== > MLC ViWi Dataset/Competition Organizers > =================== > · Ahmed Alkhateeb, Arizona State University, US > · Muhammad Alrabeiah, Arizona State University, US
