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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 81–90 of 100 papers

TitleStatusHype
Pareto Self-Supervised Training for Few-Shot Learning—0
Perception Reinforcement Using Auxiliary Learning Feature Fusion: A Modified Yolov8 for Head Detection—0
Point-TTA: Test-Time Adaptation for Point Cloud Registration Using Multitask Meta-Auxiliary Learning—0
Deep Auxiliary Learning for Visual Localization and OdometryCode0
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference CostCode0
Dataset2Vec: Learning Dataset Meta-FeaturesCode0
Improving CTC-based speech recognition via knowledge transferring from pre-trained language modelsCode0
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement LearningCode0
Auxiliary Learning for Self-Supervised Video Representation via Similarity-based Knowledge DistillationCode0
Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature SimilarityCode0
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