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Questions tagged [multi-task-learning]

For questions related to multi-task learning (MTL), which is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. MTL can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately.

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How to deal with losses on different scales in multi-task learning?

Say I'm training a model for multiple tasks by trying to minimize sum of losses $L_1 + L_2$ via gradient descent. If these losses are on a different scale, the one whose range is greater will dominate ...
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How do I format task features with a one-hot task identification vector to ensure separate weight matrices for each task in multi-task RL?

I am on Lecture 2 of Stanford CS330 Multi-Task and Meta-learning, and on slide 10, the professor describes using a one-hot input vector to represent the task, and she also explained that there would ...
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Multi-objective training vs Transfer learning - pros and cons

I'm solving a sequential prediction task that has multiple features attached to each timestamp, and my goal is to predict one of them. However, the feature's label is highly imbalanced: only about 4% ...