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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 41–50 of 100 papers

TitleStatusHype
LitCall: Learning Implicit Topology for CNN-based Aortic Landmark Localization—0
Meta-Auxiliary Learning for Adaptive Human Pose Prediction—0
Introducing Depth into Transformer-based 3D Object Detection—0
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods—0
Enhancing Deep Knowledge Tracing with Auxiliary TasksCode0
Benchmark for Uncertainty & Robustness in Self-Supervised LearningCode0
IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection—0
Auxiliary Learning as a step towards Artificial General Intelligence—0
Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications—0
Federated Learning with Server Learning: Enhancing Performance for Non-IID Data—0
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