Free access to Biometrics paper on Structural Learning and Integrative Decomposition of Multi‐View Data

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  • Date: 09 September 2019

Each week, we select a recently published article and offer either free access or highlight a recent open access publication. This week's paper is from Biometrics and is available to read at the link below:

Structural Learning and Integrative Decomposition of Multi‐View Data

Irina Gaynanova and Gen Li

Biometrics, Accepted Articles

thumbnail image: Free access to Biometrics paper on Structural Learning and Integrative Decomposition of Multi‐View Data

The increased availability of the multi‐view data (data on the same samples from multiple sources) has led to strong interest in models based on low‐rank matrix factorizations. These models represent each data view via shared and individual components, and have been successfully applied for exploratory dimension reduction, association analysis between the views, and consensus clustering. Despite these advances, there remain challenges in modeling partially‐shared components, and identifying the number of components of each type (shared/partially‐shared/individual). We formulate a novel linked component model that directly incorporates partially‐shared structures. We call this model SLIDE for Structural Learning and Integrative DEcomposition of multi‐view data.

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