论文信息 - Two Methods for Sparsifying Probabilistic Canonical Correlation Analysis

Two Methods for Sparsifying Probabilistic Canonical Correlation Analysis

We have recently developed several ways of performing Canonical Correlation Analysis [1,5,7,4] with probabilistic methods rather than the standard statistical tools. However, the computational demands of training such methods scales with the square of the number of samples, making these methods uncompetitive with e.g. artificial neural network methods [3,2]. In this paper, we examine two recent developments which sparsify probabilistic methods of performing canonical correlation analysis.

Colin Fyfe | Gayle Leen | C. Fyfe | Gayle Leen

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