<--- Back to Details
First PageDocument Content
Multivariate statistics / Matrix theory / Matrices / Abstract algebra / Manifold alignment / Nonlinear dimensionality reduction / Eigenvalues and eigenvectors / Manifold / Eigendecomposition of a matrix / Algebra / Mathematics / Linear algebra
Date: 2008-05-07 00:56:55
Multivariate statistics
Matrix theory
Matrices
Abstract algebra
Manifold alignment
Nonlinear dimensionality reduction
Eigenvalues and eigenvectors
Manifold
Eigendecomposition of a matrix
Algebra
Mathematics
Linear algebra

Add to Reading List

Source URL: people.cs.umass.edu

Download Document from Source Website

File Size: 281,51 KB

Share Document on Facebook

Similar Documents

Journal of Machine Learning Research490 Submitted 4/09; Revised 12/09; Published 2/10 Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization

DocID: 1ubJI - View Document

Statistics / Networks / Learning / Systems science / Statistical models / Systems biology / Machine learning / Bayesian network / Gene regulatory network / Nir Friedman / Gaussian process / Nonlinear dimensionality reduction

PROBABILISTIC MODELING OF GENE REGULATORY NETWORKS FROM DATA Thesis submitted for the degree “Doctor of Philosophy”

DocID: 1rpbq - View Document

Multivariate statistics / Numerical analysis / Statistics / Applied mathematics / Dimension reduction / T-distributed stochastic neighbor embedding / Computational statistics / Nonlinear dimensionality reduction / Mathematical optimization / Dimensionality reduction / Deep learning / Artificial neural network

Fast Optimization for t-SNE Laurens van der Maaten Department of Computer Science and Engineering, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093, USA Pattern Recognition & Bioinformatics Lab,

DocID: 1r6Fd - View Document

Algebra / Mathematics / Multivariate statistics / Numerical analysis / Numerical linear algebra / Iterative methods / Dimension reduction / Principal component analysis / Singular value decomposition / Stochastic optimization / Nonlinear dimensionality reduction / Sparse dictionary learning

I will discuss recent work on randomized algorithms for low-rank approximation and principal component analysis (PCA). The talk will focus on efforts that move beyond the extremely fast, but relatively crude approximatio

DocID: 1qZFc - View Document

Mathematics / Statistics / Dimension reduction / Topology / Multivariate statistics / Computational statistics / Machine learning / Dimension / Nonlinear dimensionality reduction / Isomap / Semidefinite embedding / Embedding

Unsupervised Image Embedding Using Nonparametric Statistics Guobiao Mei University of California, Riverside Abstract

DocID: 1qUPd - View Document