22 citations · 69 across the 14 of their papers we have counts for
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cs.LG2020
Meta-Learning of Structured Task Distributions in Humans and Machines
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen +2
In recent years, meta-learning, in which a model is trained on a family of tasks (i.e. a task distribution), has emerged as an approach to training neural networks to perform tasks…
cs.LG2020
Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks
Sachin Ravi, Sebastian Musslick, Maia Hamin +2
The terms multi-task learning and multitasking are easily confused. Multi-task learning refers to a paradigm in machine learning in which a network is trained on various related ta…