WMLSPWiCSR @ IJCAI 2019: Workshop on Machine Learning for Signal Processing in Wireless Communications, Sensing and Radar Macao, China, August 11, 2019 |
Conference website | https://wmlsp.github.io |
Submission link | https://easychair.org/conferences/?conf=wmlspwicsrijcai2019 |
Submission deadline | May 20, 2019 |
Acceptance notification | June 3, 2019 |
Artificial Intelligence (AI) and Machine Learning (ML) approaches, well known from Computer Science
disciplines, are beginning to emerge in the RF Signal Processing, Communications and Networking
domains. However, there are various challenges arising in the application of Machine Learning to RF
signals, such as inherently high data rates, sensitivity to environmental effects (noise, multi-path,
interference etc), presence of multi-scale features in both frequency and time domains, to name a
few. Also, in contrast to the image and text processing domains, the scarcity of large public
repositories of standardized RF signal data makes it harder for academic and industry researchers to
test and validate their algorithms in a robust, reproducible, and scalable fashion. The goal of this
workshop is to bring together researchers from the RF Signal Processing and Machine Learning
communities, showcase state-of-the-art Machine Learning approaches applicable in the RF domain,
and provide a forum for discussing cross-disciplinary ideas to address present and future challenges.
Submission Guidelines
Submissions should generally follow the IJCAI formatting requirements EXCEPT
- submitted papers should contain the author names (reviewing will *not* be anonymous)
- the page limit is 6 pages of text (including graphics) plus one page for references, however it is recommended that the initial submission be slightly shorter to accommodate possible reviewers' comments/suggestions.
Also note that a separate set of submission deadlines applies for this workshop.
Papers rejected from the main IJCAI conference are welcome for submission here, including papers simultaneously going through the appeal process.
Formatting style files can be found here.
Submissions will be accepted through EasyChair
List of Topics
Topics of interest include, but are not limited to:
- Machine Learning for blind channel and signal characterization
- Machine Learning for source separation
- Machine Learning for RF signal classification
- Machine Learning for cognitive radio communications, for instance spectrum awareness, or
optimization of spectrum usage dynamics and spectrum access control - Machine Learning for cognitive radio communications, for instance spectrum awareness, or
optimization of spectrum usage dynamics and spectrum access control - Quality of unsupervised learning with corrupted, censored and missing spectrum sensing
samples - Privacy-preserving Machine Learning for cognitive radio communications, for instance in 5G
cellular networks - Machine Learning for RF-based geo-location
- Distributed learning in collaborative autonomous networked multi-agent systems
- Adversarial Machine Learning techniques applied to RF systems
- Reinforcement learning in wireless communication and sensor networks
- Transfer Learning for wireless communication and sensor networks
- Visual analysis of learned features in Deep Learning for RF signal processing
- Machine Learning techniques for communications and sensing convergence
Committees
Organizing committee
- George Stantchev, Naval Research Laboratory, USA
- Bryan Nousain, Naval Research Laboratory, USA
- Jen-Tzung Chien, National Chiao Tung University, Taiwan
- Han Yu, Nanyang Technological Institute, Singapore
- Bhavani Shankar, University of Luxembourg, Luxembourg
Program Committee
Sheetal Kalyani | Indian Institute of Technology, Madras, India |
William (Chris) Headley | Virginia Institute of Technology, USA |
Alan Michaels | Virginia Institute of Technology, USA |
Sennur Ulukus | University of Maryland |
Tommaso Melodia | Northeastern University, USA |
Predrag Spasojevic | Rutgers University, USA |
Danijela Cabric | UCLA, USA |
Zhi (Gerry) Tian | George Mason University, USA |
Yue Wang | George Mason University, USA |
Silvija Kokalj-Filipovic | Perspecta Labs, USA |
Shree Krishna Sharma | University of Luxembourg, Luxembourg |
Stratis Ioannidis | Northeastern University, USA |
David Grace | University of York, UK |
Haris Gacanin | Nokia-Bell Labs, Belgium |
Keynote Speakers
- Dusit Niyato, National Technological University, Singapore
- TBD
Venue
The workshop will be held in conjunciton with IJCAI 2019 in Macao, China.
Contact
For questions about submissions please consult the Workshop's website where contact information for the organizers is available.