Multimodal representation learning: Difference between revisions

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=== Canonical-correlation analysis based methods ===
[[Canonical correlation|Canonical-correlation analysis]] (CCA) was first introduced in 1936 by [[Harold Hotelling]]<ref>{{Cite journal |last=Hotelling |first=H. |date=1936-12-01 |title=Relations Between Two Sets of Variates |url=https://academic.oup.com/biomet/article-lookup/doi/10.1093/biomet/28.3-4.321 |journal=Biometrika |language=en |volume=28 |issue=3–4 |pages=321–377 |doi=10.1093/biomet/28.3-4.321 |issn=0006-3444|url-access=subscription }}</ref> and is a fundamental approach for multimodal learning. CCA aims to find linear relationships between two sets of variables. Given two data [[Matrix (mathematics)|matrices]] <math>X \in \mathbb{R}^{n \times p} </math> and <math>Y \in \mathbb{R}^{n \times q}</math> representing different modalities, CCA finds projection vectors <math>w_x\in\mathbb{R}^p
</math> and <math>w_y\in\mathbb{R}^q </math> that maximizes the correlation between the projected variables: