000			02280nam a2200361 i 4500
001			CR9781108616799
003			UkCbUP
005			20240730160735.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			170831s2021||||enk o ||1 0|eng|d
020			_a9781108616799 (ebook)
020			_z9781108427135 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050		4	_aQA76.9.D343 _bI64 2021
082	0	4	_a006.312 _223
245	0	0	_aInformation-theoretic methods in data science / _cedited by Miguel R. D. Rodrigues, Yonina C. Eldar.
264		1	_aCambridge : _bCambridge University Press, _c2021.
300			_a1 online resource (xxi, 538 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 26 Mar 2021).
520			_aLearn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics.
650		0	_aData mining. _93907
650		0	_aInformation theory. _914256
650		0	_aMachine learning. _91831
700	1		_aRodrigues, Miguel R. D., _eeditor. _974302
700	1		_aEldar, Yonina C., _eeditor. _974303
776	0	8	_iPrint version: _z9781108427135
856	4	0	_uhttps://doi.org/10.1017/9781108616799
942			_cEBK
999			_c84087 _d84087