Towards Principled Task Grouping for Multi-Task Learning

arXiv:2402.15328v1 Announce Type: new
Abstract: This paper presents a novel approach to task grouping in Multitask Learning (MTL), advancing beyond existing methods by addressing key theoretical and practical limitations. Unlike prior studies, our approach offers a more theoretically grounded method that does not rely on restrictive assumptions for constructing transfer gains. We also propose a flexible mathematical programming formulation which can accommodate a wide spectrum of resource constraints, thus enhancing its versatility. Experimental results across diverse domains, including computer vision …

abstract arxiv assumptions beyond cs.lg key limitations multi-task learning multitask learning novel paper practical prior restrictive studies transfer type