000			02038naa a22003258i 4500
999			_c5327 _d5327
001			00005327
003			FR-PaOEC
005			20211006062617.0
006			a o d i
007			cr || |||m|n||
008			190601s2017 ||| o i|0| 0 eng d
035			_a(FR-PaOEC)
040			_aFR-PaOEC _cES-MaONT
100			_aSamek, Wojciech _93410
245	1	4	_aThe convergence of machine learning and communications / _cWojciech Samek, Slawomir Stanczak and Thomas Wiegand
260			_aGeneva : _bInternational Telecommunication Union, _c2017.
300			_a10 p.
336			_atexto (visual) _2isbdcontent
337			_aelectrónico _2isbdmedia
338			_arecurso en línea _2rdacarrier
520	3		_aThe 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.
650		0	_aTecnologías habilitadoras digitales _918
653		4	_aScience and Technology
700	1		_aStanczak, Slawomir _93363
700			_aWiegand, Thomas _93413
773	0		_04843 _tITU Journal: ICT Discoveries _gVol. 2018, no. 1, p. 49-58 _q2018:1<49 _x2616-8375
856	4	0	_aitu-ilibrary.org _uhttps://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2017-6-PDF-E.pdf _yAcceso al documento _x0 _qpdf
942			_cART _2udc