Multi-Task Learning of Gaussian Graphical Models

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A Survey on Multi-Task Learning (2017, methodology): “With a similar idea, multiple Gaussian graphical models are jointly learned in [148] by assuming joint sparsity among precision matrices via the `∞,1 regularization.”
Semi-supervised multi-task learning of structured prediction models for web information extraction (2011, background): “There has been a significant amount of work on multi-task learning [6, 14, 13, 4, 22, 16].”
Brain covariance selection: better individual functional connectivity models using population prior (2010, methodology): “[13] have applied with success a similar framework to modeling task-driven brain activity.”
Leveraging Domain Knowledge in Multitask Bayesian Network Structure Learning (2012, methodology): “Multitask learning has been applied to learn Gaussian graphical models (Honorio and Samaras 2010) and Bayesian networks (Niculescu-Mizil and Caruana 2007; Luis, Sucar, and Morales 2009).”
Feature-based transfer learning with real-world applications (2010, background): “• Transfer learning for other tasks Besides classification, regression, clustering and dimensionality reduction, transfer learning has also been proposed for other tasks, such as metric learning [221, 226], structure learning [79] and online learning [227].”