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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 21–30 of 100 papers

TitleStatusHype
Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning—0
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference CostCode0
Meta-Auxiliary Learning for Micro-Expression Recognition—0
HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression—0
Learning Multiple Representations with Inconsistency-Guided Detail Regularization for Mask-Guided Matting—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation—0
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific AdaptationCode0
Fast Adaptation for Human Pose Estimation via Meta-Optimization—0
Mitigate Domain Shift by Primary-Auxiliary Objectives Association for Generalizing Person ReID—0
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