Variance Reduction-Principal Component Analysis
Brief Description
The research aim is to extend the exponential convergence rate algorithm, developed by Shamir [1]. In particular, the algorithm is able to find the first eigenvector of the data matrix with exponential rate. In this research, we aim to develop an algorithm for finding the multiple eigenvetors of a matrix simultaneously with the same convergence rate.
The developed algorithm is promising, although consistent convergence is not achieved. Hence, the further research is required. More details on the algorithm and significant results is provided in the report below.
Contributors
Ziyu Wang & Tan Bui-Thanh
Report
Variance Reduction-Principle Component Analysis
Reference
[1] Shamir, O. A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate.arXiv:1409.2848, 2015