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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 41–50 of 100 papers

TitleStatusHype
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation—0
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods—0
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration—0
Deep auxiliary learning for visual localization using colorization task—0
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning—0
DistillPose: Lightweight Camera Localization Using Auxiliary Learning—0
DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning—0
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation—0
Enhancing Deep Knowledge Tracing with Auxiliary Tasks—0
Enhancing Sequential Recommendation with Graph Contrastive Learning—0
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