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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 1–10 of 100 papers

TitleStatusHype
SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-TuningCode0
Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation—0
DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning—0
LAL: Enhancing 3D Human Motion Prediction with Latency-aware Auxiliary Learning—0
SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image SegmentationCode0
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions—0
Self-supervised Auxiliary Learning for Texture and Model-based Hybrid Robust and Fair Featuring in Face Analysis—0
Learning Representation for Multitask learning through Self Supervised Auxiliary learning—0
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement LearningCode0
Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning—0
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