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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 76–100 of 100 papers

TitleStatusHype
Auxiliary Learning for Named Entity Recognition with Multiple Auxiliary Biomedical Training Data—0
Auxiliary learning induced graph convolutional networks—0
Auxiliary Tasks and Exploration Enable ObjectGoal Navigation—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation—0
Boost Test-Time Performance with Closed-Loop Inference—0
Bootstrapped Representations in Reinforcement Learning—0
Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention—0
Introducing Depth into Transformer-based 3D Object Detection—0
Deep auxiliary learning for visual localization using colorization task—0
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning—0
DistillPose: Lightweight Camera Localization Using Auxiliary Learning—0
DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning—0
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation—0
Enhancing Sequential Recommendation with Graph Contrastive Learning—0
Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications—0
Fast Adaptation for Human Pose Estimation via Meta-Optimization—0
Federated Learning with Server Learning: Enhancing Performance for Non-IID Data—0
Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks—0
Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling—0
IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection—0
Improving Noise Robustness of Contrastive Speech Representation Learning with Speech Reconstruction—0
JigsawGAN: Auxiliary Learning for Solving Jigsaw Puzzles with Generative Adversarial Networks—0
Joint learning of interpretation and distillation—0
LAL: Enhancing 3D Human Motion Prediction with Latency-aware Auxiliary Learning—0
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