02038naa a22003258i 4500 5327 5327 00005327 FR-PaOEC 20211006062617.0 a o d i cr || |||m|n|| 190601s2017 ||| o i|0| 0 eng d (FR-PaOEC) FR-PaOEC ES-MaONT Samek, Wojciech 3410 The convergence of machine learning and communications / Wojciech Samek, Slawomir Stanczak and Thomas Wiegand Geneva : International Telecommunication Union, 2017. 10 p. texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier The areas of machine learning and communication technology are converging. Today's communication systems generate a large amount of traffic data, which can help to significantly enhance the design and management of networks and communication components when combined with advanced machine learning methods. Furthermore, recently developed end-to-end training procedures offer new ways to jointly optimize the components of a communication system. Also, in many emerging application fields of communication technology, e.g., smart cities or Internet of things, machine learning methods are of central importance. This paper gives an overview of the use of machine learning in different areas of communications and discusses two exemplar applications in wireless networking. Furthermore, it identifies promising future research topics and discusses their potential impact. Tecnologías habilitadoras digitales 18 Science and Technology Stanczak, Slawomir 3363 Wiegand, Thomas 3413 4843 ITU Journal: ICT Discoveries Vol. 2018, no. 1, p. 49-58 2018:1<49 2616-8375 itu-ilibrary.org https://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2017-6-PDF-E.pdf Acceso al documento 0 pdf ART udc 0 0 0 3 1 6277 01 01 online 2019-09-12 0 1000020175576 2019-09-12 00:00:00 2019-09-12 ART pdf