The Benefit of Multitask Representation Learning

Understand

We discuss a general method to learn data representations from multiple tasks.

• We provide a justification for this method in both settings of multitask learning and learning-to-learn.
• The method is illustrated in detail in the special case of linear feature learning.
• Conditions on the theoretical advantage offered by multitask representation learning over independent task learning are established.