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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
Benchmark for Uncertainty & Robustness in Self-Supervised LearningCode0
IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection—0
Auxiliary Learning as a step towards Artificial General Intelligence—0
Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications—0
Federated Learning with Server Learning: Enhancing Performance for Non-IID Data—0
Test-time Adaptation for Real Image Denoising via Meta-transfer Learning—0
Meta Auxiliary Learning for Low-resource Spoken Language Understanding—0
Enhancing Sequential Recommendation with Graph Contrastive Learning—0
AANG: Automating Auxiliary LearningCode0
Auxiliary Learning for Named Entity Recognition with Multiple Auxiliary Biomedical Training Data—0
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