000			02474nam a22003738a 4500
001			CR9781139042918
003			UkCbUP
005			20171019114426.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			110302s2011||||enk s ||1 0|eng|d
020			_a9781139042918 (ebook)
020			_z9780521192248 (hardback)
040			_aUkCbUP _cUkCbUP _erda
050	0	0	_aQ325.5 _b.S28 2012
082	0	0	_a006.3/1 _223
245	0	0	_aScaling up Machine Learning : _bParallel and Distributed Approaches / _cEdited by Ron Bekkerman, Mikhail Bilenko, John Langford.
264		1	_aCambridge : _bCambridge University Press, _c2011.
300			_a1 online resource (492 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 09 Oct 2015).
520			_aThis book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algorithms and deep dives into several applications make the book equally useful for researchers, students and practitioners.
650		0	_aMachine learning
650		0	_aData mining
650		0	_aParallel algorithms
650		0	_aParallel programs (Computer programs)
700	1		_aBekkerman, Ron, _eeditor of compilation.
700	1		_aBilenko, Mikhail, _eeditor of compilation.
700	1		_aLangford, John, _eeditor of compilation.
776	0	8	_iPrint version: _z9780521192248
856	4	0	_uhttp://dx.doi.org/10.1017/CBO9781139042918
999			_c225616 _d225616