Training School on Machine Learning for Communications

23-25 September 2019 // Paris, France

Within the last few years, research on machine learning for communications has demonstrated its potential to significantly improve different aspects of communication systems. In wireless communications, emerging Beyond-5G technologies bring complex optimization problems, complex modeling and low complexity processing requirements. Machine learning methods and data-driven algorithms have recently proposed new approaches of modeling, designing, optimizing and implementing communication systems.

As part of the activities carried out by the IEEE ComSoc Machine Learning for Communications Emerging Technologies Initiative, the goal of this training school is to present the latest advances in the field of machine learning for communications and to further prospect this emerging research field. Lectures from internationally-renowned researchers from academia and industry will be given during this three-day training school.

Ph.D. students and early-stage researchers in the wide field of communications are particularly encouraged to attend. Background in the machine learning field is not mandatory.

Location

  • Paris, France

Date

  • September 23-25, 2019

Organization Committee

Marwa Chafii

ENSEA

Slawomir Stanczak

TU Berlin

Jakob Hoydis

Nokia Bell Labs

Marco Di Renzo

CentraleSupélec

Marios Kountouris

EURECOM