"Statistical Methods Generalizing Principal Component Analysis to Non-Euclidean Spaces"

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Book	Author(s)	Year	Publisher
Principal Component Analysis Methods, Applications, and Technology	VIRGINIA GRAY	2017
Principal Component Analysis	I. T. Jolliffe	2nd ed. 2002	Springer New York
Principal Component Analysis	I. T. Jolliffe	1986	Springer New York
Topological Methods in Euclidean Spaces	G.L. Naber	1980	Cambridge University Press
Topological methods in Euclidean spaces	Naber, Gregory L	1980	Cambridge University Press
Qα Analysis on Euclidean Spaces	Jie Xiao	2019	De Gruyter
Introduction to Fourier analysis on Euclidean spaces	Elias M. Stein	1975	Princeton University Press
Generalized Principal Component Analysis	René Vidal; Yi Ma; Shankar Sastry	1st ed. 2016	Springer New York
GPU Ray Tracing in Non-Euclidean Spaces	Novello Tiago; da Silva Vinícius; Velho Luiz		Springer International Publishing
Principal Component Analysis - Engineering Applications	P. Sanguansat	2012	Intech
Principal component analysis - multidisciplinary applications	Parinya Sanguansat	2012	InTech
Analysis of Spherical Symmetries in Euclidean Spaces	Claus Müller	1998	Springer New York
Principal Component Analysis Networks and Algorithms	Xiangyu Kong; Changhua Hu; Zhansheng Duan	1st ed. 2017	Springer Nature Singapore
Principal Component Analysis [data, math. anal. ]	P. Sanguansat	2012	Intech
Euclidean and non-euclidean geometries /	Noronha, Maria Helena.	[2002], ©2002.	Prentice Hall,
Harmonic analysis in Euclidean spaces: [dedicated to Nestor M. Rivière]	Symposium in Pure Mathematics (1978 Williams College)	1979	American Mathematical Society
Introduction to Non-Euclidean Geometry	Wolfe, Harold E	2013	Dover Publications
Introduction to non-Euclidean geometry	Harold Eichholtz Wolfe	©1945	Holt, Rinehart and Winston
Introduction to Non-Euclidean Geometry	H. Wolfe; Harold Eichholtz Wolfe	January 1995	Harcourt
Introduction to non-Euclidean geometry	Harold Eichholtz Wolfe	1945	Holt, Rinehart and Winston
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Statistical Methods Generalizing Principal Component Analysis to Non-Euclidean Spaces	Stephan Huckemann; Benjamin Eltzner	Handbook of Variational Methods for Nonlinear Geometric Data	Philipp Grohs; Martin Holler; Andreas Weinmann	1st ed. 2020	Springer International Publishing
(Semi-)Intrinsic Statistical Analysis on Non-Euclidean Spaces	Stephan F. Huckemann	Advances in Complex Data Modeling and Computational Methods in Statistics	Anna Maria Paganoni; Piercesare Secchi	2015	Springer International Publishing
Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning	Mandy Lange; David Nebel; Thomas Villmann	Artificial Intelligence and Soft Computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part I	Leszek Rutkowski; Marcin Korytkowski; Rafał Scherer; Ryszard Tadeusiewicz; Lotfi A. Zadeh; Jacek M. Zurada	2014	Springer International Publishing
Principal Component Analysis: Application to Statistical Process Control	Gilbert Saporta; Ndèye Niang	Data Analysis	Gérard Govaert	2009	John Wiley & Sons
Non-Euclidean Principal Component Analysis and Oja’s Learning Rule – Theoretical Aspects	Michael Biehl; Marika Kästner; Mandy Lange; Thomas Villmann	Advances in Self-Organizing Maps: 9th International Workshop, WSOM 2012 Santiago, Chile, December 12-14, 2012 Proceedings	Pablo A. Estévez; José C. Príncipe; Pablo Zegers	2013	Springer Berlin Heidelberg
Principal Component Analysis	Leo H. Chiang; Evan L. Russell; Richard D. Braatz	Fault Detection and Diagnosis in Industrial Systems	L.H. Chiang; E.L. Russell; R.D. Braatz	2001	Springer London
Principal Component Analysis	Jianzhong Wang	Geometric Structure of High-Dimensional Data and Dimensionality Reduction	Jianzhong Wang	2012	Springer Berlin Heidelberg
Principal Component Analysis		Encyclopedia of Biophysics	Gordon Roberts	2013	Springer Berlin Heidelberg
Principal Component Analysis	Ron Wehrens	Chemometrics with R: Multivariate Data Analysis in the Natural Sciences and Life Sciences	Ron Wehrens	2011	Springer Berlin Heidelberg
Principal Component Analysis		Encyclopedia of Machine Learning and Data Mining	Claude Sammut; Geoffrey I. Webb	2nd ed. 2017	Springer US
Principal Component Analysis	Paolo Giordani	Encyclopedia of Social Network Analysis and Mining	Reda Alhajj; Jon Rokne	2014	Springer New York
Principal Component Analysis	Evan L. Russell; Leo H. Chiang; Richard D. Braatz	Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes	Evan L. Russell; Leo H. Chiang; Richard D. Braatz	2000	Springer London
Principal Component Analysis	Hans Wackernagel	Multivariate Geostatistics: An Introduction with Applications	Hans Wackernagel	1995	Springer Berlin Heidelberg
Principal Component Analysis	Ron Johnston	Encyclopedia of Quality of Life and Well-Being Research	Alex C. Michalos	2014	Springer Netherlands
Principal Component Analysis	Ian Jolliffe	International Encyclopedia of Statistical Science	Miodrag Lovric	2011	Springer Berlin Heidelberg
Principal Component Analysis	Hans-Peter Deutsch	Derivatives and Internal Models	H. Deutsch	4th ed. 2009	Palgrave Macmillan UK
Principal Component Analysis	Yasha Hasija; Rajkumar Chakraborty	Hands-On Data Science for Biologists Using Python	Yasha Hasija; Rajkumar Chakraborty	2021	Routledge
Principal Component Analysis	Andreas Pöge; Jost Reinecke	Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods	Uwe Engel; Anabel Quan-Haase; Sunny Liu; Lars Lyberg	2021	Routledge
Principal Component Analysis	Caterina Labrín; Francisco Urdinez	R for Political Data Science: A Practical Guide	Francisco Urdinez; Andres Cruz	2020	Routledge
Principal Component Analysis	Sadanori Konishi	Introduction to Multivariate Analysis: Linear and Nonlinear Modeling	Sadanori Konishi	2014	Routledge
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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