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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 MULTI-TASK LEARNING

Auxiliary Learning by Implicit Differentiation

ICLR 2021 AvivNavon/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

Dataset2Vec: Learning Dataset Meta-Features

27 May 2019hadijomaa/dataset2vec

As a data-driven approach, meta-learning requires meta-features that represent the primary learning tasks or datasets, and are estimated traditonally as engineered dataset statistics that require expert domain knowledge tailored for every meta-task.

AUXILIARY LEARNING FEW-SHOT LEARNING HYPERPARAMETER OPTIMIZATION

Auxiliary Tasks and Exploration Enable ObjectNav

8 Apr 2021joel99/objectnav

We instead re-enable a generic learned agent by adding auxiliary learning tasks and an exploration reward.

AUXILIARY LEARNING

Learning Object Placements For Relational Instructions by Hallucinating Scene Representations

23 Jan 2020mees/AIS-Alexa-Robot

One particular requirement for such robots is that they are able to understand spatial relations and can place objects in accordance with the spatial relations expressed by their user.

AUXILIARY LEARNING HUMAN ROBOT INTERACTION ROBOTIC GRASPING SCENE GENERATION SPATIAL RELATION RECOGNITION