Hello. I am Ammar ahmad khan, telecommunication engineer from pakistan. I have also interest in machine learning. I would like to know if we can attend this ieee machine learning and communication workshop online ?
Kind regards On Sat, 25 Jan 2020, 11:00 pm Adrian Musceac, <[email protected]> wrote: > Hi, > I hope I'm not spamming, but the below message circulated on the GR list > seems to fit well with the latest work done in Codec2. > > Regards, > Adrian > > ------------------------------ > *From:* "West, Nathan" <[email protected]> > *Sent:* January 25, 2020 3:20:49 PM UTC > *To:* [email protected] > *Subject:* Open Workshop on Machine Learning in Communications @ IEEE ICC > 2020 (Call for Contributions) > > 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/ > > =================== > 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. > 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 > > EDAS submission link: 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 > _______________________________________________ > Freetel-codec2 mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/freetel-codec2 >
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