Machine Learning under Imperfect Data: Challenges and Methods
This short survey organises representative methods around representative methods around reconstruction and generation, rebalancing and representation calibration, learning with limited supervision, adaptation across domains and modalities, and reliability under distribution change.
Masoumeh Zareapoor
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