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Auxiliary Learning

3 papers with code · Methodology
Subtask of Transfer Learning

Auxiliary learning aims to find or design auxiliary tasks which can improve the performance on one or some primary tasks.

( Image credit: Self-Supervised Generalisation with Meta Auxiliary Learning )

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Greatest papers with code

Self-Supervised Generalisation with Meta Auxiliary Learning

NeurIPS 2019 lorenmt/maxl

The loss for the label-generation network incorporates the loss of the multi-task network, and so this interaction between the two networks can be seen as a form of meta learning with a double gradient.

AUXILIARY LEARNING META-LEARNING

Self-Supervised Generalisation with Meta Auxiliary Learning

NeurIPS 2019 lorenmt/maxl

The loss for the label-generation network incorporates the loss of the multi-task network, and so this interaction between the two networks can be seen as a form of meta learning with a double gradient.

AUXILIARY LEARNING META-LEARNING MULTI-TASK LEARNING

Auxiliary Learning by Implicit Differentiation

22 Jun 2020AvivNavon/AuxiLearn

Two main challenges arise in this multi-task learning setting: (i) Designing useful auxiliary tasks; and (ii) Combining auxiliary tasks into a single coherent loss.

AUXILIARY LEARNING MULTI-TASK LEARNING SEMANTIC SEGMENTATION SMALL DATA IMAGE CLASSIFICATION