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[null,"1.","Record Nr.",null,"UNINA9910702623203321"]
[null,null,"Autore",null,"Masubuchi Koichi <1924-2016, >"]
[null,null,"Titolo",null,"Feasibility of remotely manipulated welding in space : a step in the development of novel joining technologies / / by Koichi Masubuchi [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge, Mass. : , : Massachusetts Institute of Technology, Department of Ocean Engineering"]
[{"$nulls":4},"Washington, D.C. : , : Office of Space Science and Applications, NASA Headquarters, , September 1983"]
[null,null,"Descrizione fisica",null,"1 online resource (vi, 129. pages, 132 unnumbered pages) : illustrations"]
[null,null,"Collana",null,"NASA-CR ; ; 175437"]
[null,null,"Soggetti",null,"Gas tungsten arc welding"]
[{"$nulls":4},"Large space structures"]
[{"$nulls":4},"Remote manipulator system"]
[{"$nulls":4},"Space commercialization"]
[{"$nulls":4},"Space Shuttle payloads"]
[{"$nulls":4},"Structural design criteria"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from title screen (viewed Oct. 22, 2014)."]
[{"$nulls":4},"\"September 1983.\""]
[{"$nulls":4},"\"M.I.T. OSP #93589.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,"2.","Record Nr.",null,"UNINA9910483873203321"]
[null,null,"Titolo",null,"Subspace, Latent Structure and Feature Selection : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / / edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006"]
[null,null,"ISBN",null,"3-540-34138-2"]
[null,null,"Edizione",null,"[1st ed. 2006.]"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 209 p.)"]
[null,null,"Collana",null,"Theoretical Computer Science and General Issues, , 2512-2029 ; ; 3940"]
[null,null,"Disciplina",null,"003/.1"]
[null,null,"Soggetti",null,"Algorithms"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Mathematical statistics"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Probability and Statistics in Computer Science"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Automated Pattern Recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and author index."]
[null,null,"Nota di contenuto",null,"Invited Contributions -- Discrete Component Analysis -- Overview and Recent Advances in Partial Least Squares -- Random Projection, Margins, Kernels, and Feature-Selection -- Some Aspects of Latent Structure Analysis -- Feature Selection for Dimensionality Reduction -- Contributed Papers -- Auxiliary Variational Information Maximization for Dimensionality Reduction -- Constructing Visual Models with a Latent Space Approach -- Is Feature Selection Still Necessary? -- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data -- Incorporating Constraints and Prior Knowledge into Factorization Algorithms – An Application to 3D Recovery -- A Simple Feature Extraction for High Dimensional Image Representations -- Identifying "]
[{"$nulls":4},"Feature Relevance Using a Random Forest -- Generalization Bounds for Subspace Selection and Hyperbolic PCA -- Less Biased Measurement of Feature Selection Benefits."]
[null,null,null,"Sommario/riassunto","This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005. The 9 revised full papers presented together with 5 invited papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, among others."]