Formulation of Multiple Kernel Learning Using Composite Architectures

dc.contributor.guide	Sumitra S
dc.coverage.spatial
dc.creator.researcher	Shiju S S
dc.date.accessioned	2019-03-27T06:35:27Z
dc.date.available	2019-03-27T06:35:27Z
dc.date.awarded	14.02.2019
dc.date.completed	08.03.2019
dc.date.registered	31.01.2013
dc.description.abstract	newline
dc.description.note
dc.format.accompanyingmaterial	DVD
dc.format.dimensions	22cm*30cm
dc.format.extent	xix, 105p
dc.identifier.uri	http://hdl.handle.net/10603/235231
dc.language	English
dc.publisher.institution	Department of Mathematics
dc.publisher.place	Thiruvananthapuram
dc.publisher.university	Indian Institute of Space Science and Technology
dc.relation	89
dc.rights	university
dc.source.university	University
dc.subject.keyword	Physical Sciences,Mathematics,Mathematics,Multiple kernel learning,Composite architecture,Algorithm,MKL,Kernel,Kernel hilbert space,Kernel ridge regression,Regression,Nonlinear
dc.title	Formulation of Multiple Kernel Learning Using Composite Architectures
dc.title.alternative
dc.type.degree	Ph.D.