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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
GeoAuxNet: Towards Universal 3D Representation Learning for Multi-sensor Point CloudsCode1
A Survey on Cross-Domain Sequential RecommendationCode1
RL-I2IT: Image-to-Image Translation with Deep Reinforcement LearningCode1
Learning to Recover Spectral Reflectance from RGB ImagesCode1
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation ModelsCode1
Auxiliary Learning as an Asymmetric Bargaining GameCode1
Counting with Adaptive Auxiliary LearningCode1
Auto-Lambda: Disentangling Dynamic Task RelationshipsCode1
Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic SegmentationCode1
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-LearningCode1
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