Stochastic Approximation for Canonical Correlation Analysis
نویسندگان
چکیده
We study canonical correlation analysis (CCA) as a stochastic optimization problem. We show that regularized CCA is efficiently PAC-learnable. We give stochastic approximation (SA) algorithms that are instances of stochastic mirror descent, which achieve -suboptimality in the population objective in time poly( 1 , 1 δ , d) with probability 1− δ, where d is the input dimensionality.
منابع مشابه
A Uniied Approach to Pca, Pls, Mlr and Cca
This paper presents a novel algorithm for analysis of stochastic processes. The algorithm can be used to nd the required solutions in the cases of principal component analysis (PCA), partial least squares (PLS), canonical correlation analysis (CCA) or multiple linear regression (MLR). The algorithm is iterative and sequential in its structure and uses on-line stochastic approximation to reach a...
متن کاملA learning algorithm for adaptive canonical correlation analysis of several data sets
Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of co...
متن کاملApproximation of stochastic advection diffusion equations with finite difference scheme
In this paper, a high-order and conditionally stable stochastic difference scheme is proposed for the numerical solution of $rm Ithat{o}$ stochastic advection diffusion equation with one dimensional white noise process. We applied a finite difference approximation of fourth-order for discretizing space spatial derivative of this equation. The main properties of deterministic difference schemes,...
متن کاملFunctional Canonical Analysis for Square Integrable Stochastic Processes
We study the extension of canonical correlation from pairs of random vectors to the case where a data sample consists of pairs of square integrable stochastic processes. Basic questions concerning the definition and existence of functional canonical correlation are addressed and sufficient criteria for the existence of functional canonical correlation are presented. Various properties of functi...
متن کاملCanonical correlation analysis for functional data
Classical canonical correlation analysis seeks the associations between two data sets, i.e. it searches for linear combinations of the original variables having maximal correlation. Our task is to maximize this correlation, and is equivalent to solving a generalized eigenvalue problem. The maximal correlation coefficient (being a solution of this problem) is the first canonical correlation coef...
متن کامل