Confidently Biased (ConB): A Per-sample Confidence Approach for Unsupervised Model Debiasing

Lecture notes in computer science 2026

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Authors: Massimiliano Ciranni, Aliaksandr Shcharbitski, Vittorio Murino, Vito Paolo Pastore

DOI: 10.1007/978-3-032-10185-3_7

Cited by: 0

References: 10

Fields of Study & Subjects

Domain Adaptation and Few-Shot Learning Generative Adversarial Networks and Image Synthesis Adversarial Robustness in Machine Learning

References 10