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Online Multi-Task Learning with Recursive Least Squares and Recursive Kernel Methods
March 19, 2024, 4:45 a.m. | Gabriel R. Lencione, Fernando J. Von Zuben
cs.LG updates on arXiv.org arxiv.org
Abstract: This paper introduces two novel approaches for Online Multi-Task Learning (MTL) Regression Problems. We employ a high performance graph-based MTL formulation and develop two alternative recursive versions based on the Weighted Recursive Least Squares (WRLS) and the Online Sparse Least Squares Support Vector Regression (OSLSSVR) strategies. Adopting task-stacking transformations, we demonstrate the existence of a single matrix incorporating the relationship of multiple tasks and providing structural information to be embodied by the MT-WRLS method in …
abstract arxiv cs.lg graph graph-based kernel least multi-task learning novel paper performance recursive regression squares stat.ml support type vector versions
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