Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis

@inproceedings{Ma2015FindingLS,
  title={Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis},
  author={Zhuang Ma and Yichao Lu and Dean P. Foster},
  booktitle={ICML},
  year={2015}
}
Canonical Correlation Analysis (CCA) is a widely used spectral technique for finding correlation structures in multi-view datasets. In this paper, we tackle the problem of large scale CCA, where classical algorithms, usually requiring computing the product of two huge matrices and huge matrix decomposition, are computationally and storage expensive. We… CONTINUE READING

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