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Auxiliary 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 )

Papers

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Showing 61–70 of 100 papers

TitleStatusHype
SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation—0
Self-supervised Auxiliary Learning for Texture and Model-based Hybrid Robust and Fair Featuring in Face Analysis—0
Self-supervised pre-training and contrastive representation learning for multiple-choice video QA—0
Semantic-aware Temporal Channel-wise Attention for Cardiac Function Assessment—0
Siamese Labels Auxiliary Learning—0
Test-time Adaptation for Real Image Denoising via Meta-transfer Learning—0
Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning—0
To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions—0
Auxiliary Learning for Deep Multi-task Learning—0
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation—0
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