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Found 2 papers, 1 papers with code
SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries
Inspired by natural learners, we introduce a Sparse High-level-Exclusive, Low-level-Shared feature representation (SHELS) that simultaneously encourages learning exclusive sets of high-level features and essential, shared low-level features.
Mako: Semi-supervised continual learning with minimal labeled data via data programming
This tool achieves similar performance, in terms of per-task accuracy and resistance to catastrophic forgetting, as compared to fully labeled data.
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