000			01430nam a2200289Ia 4500
003			OSt
005			20250731103149.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9781482241396
037			_cTextbook
040			_aCSL _beng _cCSL
041			_aeng
084			_aD65,8(B):9 Q5 TOR _qCSL
245		0	_aRegularization optimization kernels and support vector machines
260			_aBoca Raton : _bCRC Press. _c2015,
300			_axvii, 507p. _b: ill.
500			_aIndex 503-507p.
520			_aRegularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning.
650			_a Nonparametric _9817006
650			_a Subspaces _9817007
650			_aNonconvex proximal splitting _9817008
700			_aSuykens, Johan A K _eeditor _9817009
700			_aArgyriou, Andreas _eeditor _9817010
700			_aSignoretto, Marco _eeditor _9817011
942			_hD65,8(B):9 Q5 TOR _cTB _2CC _n0
999			_c6552 _d6552