Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation

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A Survey on Multi-Task Learning (2017, background): “Moreover, given a tree structure describing relations among tasks, the model parameter of a task corresponding to a node in the tree is enforced to be similar to that of its parent node [67].”
Learning Multi-Level Task Groups in Multi-Task Learning (2015, background): “All rights reserved. and Xu 2010; Zhang and Schneider 2010; Zhang and Yeung 2010; Zhang 2013; Zhang and Yeung 2014), and some assume the task structure is hierarchical (Daumé III 2009; Jalali et al. 2010; Görnitz et al. 2011; Lozano and Swirszcz 2012; Zweig and Weinshall 2013).”
Hierarchical Bayesian Inference and Recursive Regularization for Large-Scale Classification (2015, background): “Although there are a few works that address the scalability of these methods with a large number of training instances [Gornitz et al. 2011; Widmer et al. 2010], there is no work that focuses on scaling with a large number of classes.”
Encoding Tree Sparsity in Multi-Task Learning: A Probabilistic Framework (2014, background): “All rights reserved. and Zhang 2012), grouping related tasks (Bakker and Heskes 2003; Xue et al. 2007; Jacob, Bach, and Vert 2008; Kumar and Daume III 2012), and learning with hierarchical task structure (Kim and Xing 2010; Görnitz et al. 2011; Zweig and Weinshall 2013).”