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Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models

Arshdeep Sekhon, Beilun Wang, View ORCID ProfileYanjun Qi
doi: https://doi.org/10.1101/716852
Arshdeep Sekhon
Department of Computer Science, University of Virginia, Computer Science Department,
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Beilun Wang
Department of Computer Science, University of Virginia, Computer Science Department,
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Yanjun Qi
Department of Computer Science, University of Virginia, Computer Science Department,
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  • ORCID record for Yanjun Qi
  • For correspondence: yanjun@virginia.edu
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Abstract

We focus on integrating different types of extra knowledge (other than the observed samples) for estimating the sparse structure change between two p-dimensional Gaussian Graphical Models (i.e. differential GGMs). Previous differential GGM estimators either fail to include additional knowledge or cannot scale up to a high-dimensional (large p) situation. This paper proposes a novel method KDiffNet that incorporates Additional Knowledge in identifying Differential Networks via an Elementary Estimator. We design a novel hybrid norm as a superposition of two structured norms guided by the extra edge information and the additional node group knowledge. KDiffNet is solved through a fast parallel proximal algorithm, enabling it to work in large-scale settings. KDiffNet can incorporate various combinations of existing knowledge without re-designing the optimization. Through rigorous statistical analysis we show that, while considering more evidence, KDiffNet achieves the same convergence rate as the state-of-the-art. Empirically on multiple synthetic datasets and one real-world fMRI brain data, KDiffNet significantly outperforms the cutting edge baselines with regard to the prediction performance, while achieving the same level of time cost or less.

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  • http://jointnets.org/

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 28, 2019.
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Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models
Arshdeep Sekhon, Beilun Wang, Yanjun Qi
bioRxiv 716852; doi: https://doi.org/10.1101/716852
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Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models
Arshdeep Sekhon, Beilun Wang, Yanjun Qi
bioRxiv 716852; doi: https://doi.org/10.1101/716852

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