000			03033cam a2200409 i 4500
001			21733306
003			OSt
005			20221020112128.0
008			160912s2019 nyua||| b |||1 0|eng d
010			_a 2019751026
020			_a9781484236574 _qpaperback
020			_qebook _z9781484236581
024	7		_a10.1007/978-3-319-45174-9 _2doi
035			_a(DE-He213)978-3-319-45174-9
040			_aDLC _beng _epn _erda _cDLC _drda _dUOC
072		7	_aCOM016000 _2bisacsh
072		7	_aUYQP _2bicssc
072		7	_aUYQP _2thema
082	0	0	_a004.165 _223 _bLEI
100			_aEtaati, Leila _eauthor. _936
245	1	0	_aMachine Learning with Microsoft Technologies : _bSelecting the Right Architecture and Tools for Your Project / _cLeila Etaati.
264		1	_aNew York, NY : _bApress, _c[2019].
264		4	_c© 2019 by Leila Etaati.
300			_axv, 365 Pages : _bIllustrations ; _c20 cm.
336			_atext _btxt _2rdacontent
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
500			_aIncludes index
505	0		_aNetworks and Decoding -- Multi-Task Learning for Interpretation of Brain Decoding Models -- The New Graph Kernels on Connectivity Networks for Identification of MCI -- Mapping Tractography Across Subjects -- Speech -- Automated speech analysis for psychosis evaluation -- Combining different modalities in classifying phonological categories -- Clinics and cognition -- Label-alignment-based Multi-task Feature Selection for Multimodal Classification of Brain Disease -- Leveraging Clinical Data to Enhance Localization of Brain Atrophy -- Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization -- Causality and time-series -- Classification-based Causality Detection in Time Series -- Fast and Improved SLEX Analysis of High-dimensional Time Series -- Best paper awards: MLINI 2013 -- Predicting Short-Term Cognitive Change from Longitudinal Neuroimaging Analysis -- Hyperalignment of Multi-Subject fMRI Data by Synchronized Projections -- An oblique approach to prediction of conversion to Alzheimer's Disease with multikernel Gaussian Processes.
520			_aThis book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, Canada, in December 2014 as a satellite event of the 11th annual conference on Neural Information Processing Systems, NIPS 2014. The 10 MLINI 2014 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: networks and decoding; speech; clinics and cognition; and causality and time-series. In addition, the book contains the 3 best papers presented at MLINI 2013.
650		0	_aArtificial intelligence. _938
650		0	_aMachine learning. _977
650		0	_aMicrosoft software. _93571
650		0	_aPython (Computer program language) _998
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c469 _d469