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Found 3 papers, 1 papers with code
Hacking Task Confounder in Meta-Learning
However, our experiments reveal an unexpected result: there is negative knowledge transfer between tasks, affecting generalization performance.
Unleash Model Potential: Bootstrapped Meta Self-supervised Learning
The long-term goal of machine learning is to learn general visual representations from a small amount of data without supervision, mimicking three advantages of human cognition: i) no need for labels, ii) robustness to data scarcity, and iii) learning from experience.
Towards the Sparseness of Projection Head in Self-Supervised Learning
In recent years, self-supervised learning (SSL) has emerged as a promising approach for extracting valuable representations from unlabeled data.
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