posted by user: zbking || 3021 views || tracked by 8 users: [display]

ITW 2016 : IEEE Information Theory Workshop

FacebookTwitterLinkedInGoogle

Link: http://sigproc.eng.cam.ac.uk/ITW2016/WebHome
 
When Sep 11, 2016 - Sep 14, 2016
Where Cambridge, UK
Submission Deadline Mar 13, 2016
Notification Due Jun 12, 2016
Final Version Due Jul 31, 2016
Categories    information theory   communications   networking
 

Call For Papers

The IEEE Information Theory Workshop (ITW) covers all topics broadly related to information theory. In addition to its traditional scope, the 2016 edition will also focus on the intersections of information theory, machine learning, and compressed sensing. The conference will take place at Robinson College, the youngest of the Cambridge colleges founded in 1979, offering modern dedicated conference facilities in a cosy residential setup and easy access to the sights and attractions in central Cambridge that lie within a 10 minutes walk of the college.


Important Dates:

Paper Submission Deadline: 13 March 2016
Acceptance Notification: 12 June 2016
Final Paper Submission: 31 July 2016

Related Resources

IEEE ISNCC 2018   2018 IEEE International Symposium on Networks, Computers and Communications
CCSEIT 2018   8th International Conference on Computer Science, Engineering and Information Technology
ICCVBIC 2018   IEEE International Conference On Computational Vision and Bio Inspired Computing
DMS 2018   9th International Conference on Database Management Systems
RCIS 2018   IEEE 12th International Conference on Research Challenges in Information Science
ECIJ 2017   Electrical & Computer Engineering: An International Journal
IEEE Multimedia 5G 2018   IEEE Multimedia Special issue on 5G Multimedia Communications: Theory, Technology, and Application
ICVIP 2017   2017 International Conference on Video and Image Processing (ICVIP 2017)--Ei and Scopus
ICKEA--IEEE, Ei Compendex & Scopus 2018   2018 3rd International Conference on Knowledge Engineering and Applications (ICKEA 2018)--IEEE, Ei Compendex & Scopus
COLT 2018   Computational Learning Theory