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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 61–70 of 100 papers

TitleStatusHype
Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler—0
Novel Natural Language Summarization of Program Code via Leveraging Multiple Input Representations—0
Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature SimilarityCode0
Improving Noise Robustness of Contrastive Speech Representation Learning with Speech Reconstruction—0
Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction PredictionCode0
DistillPose: Lightweight Camera Localization Using Auxiliary Learning—0
Deep auxiliary learning for visual localization using colorization task—0
Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning—0
Auxiliary learning induced graph convolutional networks—0
Meta Auxiliary Learning for Facial Action Unit Detection—0
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