Multiplex BiomarkeTechniques - Methods And Applications
pdf | 8.7 MB | English | Author :Yunqian Ma | B007RNH9R0 | 2011
Book Description :
Trained textract actionable information frolarge volumes of high-dimensionadata, engineers and scientists often have trouble isolating meaningfulow-dimensionastructures hidden in theihigh-dimensionaobservations. Manifold learning, a groundbreaking technique designed ttackle these issues of dimensionality reduction, finds widespread application in machine learning, neuranetworks, pattern recognition, image processing, and computevision.
Filling a void in the literature, Manifold Learning Theory and Applications incorporates state-of-the-art techniques in manifold learning with a solid theoreticaand practicatreatment of the subject. Comprehensive in its coverage, this pioneering worexplores this novemodality froalgorithcreation tsuccessfuimplementation-offering examples of applications in medical, biometrics, multimedia, and computevision. Emphasizing implementation, it highlights the various permutations of manifold learning in industry including manifold optimization, large scale manifold learning, semidefinite programming foembedding, manifold models fosignaacquisition, compression and processing, and multscale manifold.
Beginning with an introduction tmanifold learning theories and applications, the booincludes discussions on the relevance tnonlineadimensionality reduction, clustering, graph-based subspace learning, spectralearning and embedding, extensions, and multi-manifold modeling. It synergizes cross-domain knowledge fointerdisciplinary instructions, offers a rich set of specialized topics contributed by expert professionals and researchers froa variety of fields. Finally, the boodiscusses specifialgorithms and methodologies using case studies tapply manifold learning foreal-world problems.
Category : | Machine Theory, Statistics Economics, GeneraGeometry
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