Foundations of Data Science 1 John Hopcroft Ravindran Kannan

First Page		Document Content
Date: 2014-08-25 17:40:07 Linear algebra Multivariate statistics Data analysis Matrix theory Singular value decomposition Vector space model Principal component analysis Cluster analysis Hidden Markov model Algebra Statistics Mathematics		Foundations of Data Science 1 John Hopcroft Ravindran Kannan Add to Reading List Source URL: research.microsoft.com Download Document from Source Website File Size: 1,98 MB Share Document on Facebook

	Principal Component Analysis on non-Gaussian Dependent Data Fang Han Johns Hopkins University, 615 N.Wolfe Street, Baltimore, MDUSA Han Liu Princeton University, 98 Charlton Street, Princeton, NJUSA DocID: 1vdC9 - View Document
	Generalized Principal Component Analysis (GPCA)∗ Ren´e Vidal† Yi Ma‡ Shankar Sastry† † Department of EECS, University of California, Berkeley, CA 94720 DocID: 1uYRE - View Document
	A. Krisciukaitis et al.: Efficiency Evaluation of Autonomic Heart Control by Using the Principal Component Analysis of ECG P-Wave, en 9 en9 Efficiency Evaluation of Autonomic Heart Control by Using DocID: 1tOkO - View Document
	Full Regularization Path for Sparse Principal Component Analysis Alexandre d’Aspremont, Francis Bach & Laurent El Ghaoui, Princeton University, INRIA/ENS Ulm & U.C. Berkeley Support from NSF, DHS and Google. DocID: 1tMMK - View Document
	Binary Principal Component Analysis in the Netflix Collaborative Filtering Task DocID: 1tMJC - View Document