# Iterative Aggregation Method for Solving Principal Component Analysis Problems

arXiv: https://arxiv.org/abs/1602.08800 · HTML: https://mlsanity.com/paper/1602.08800/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Feb 2016.

## Built on by (most cited first, 1 of 1)

- [Do Large Multimodal Models Solve Caption Generation for Scientific Figures? Lessons Learned from SciCap Challenge 2023](https://mlsanity.com/paper/2501.19353/) (2025)

## Abstract (arXiv)

Motivated by the previously developed multilevel aggregation method for solving structural analysis problems a novel two-level aggregation approach for efficient iterative solution of Principal Component Analysis (PCA) problems is proposed. The course aggregation model of the original covariance matrix is used in the iterative solution of the eigenvalue problem by a power iterations method. The method is tested on several data sets consisting of large number of text documents.