… Survey on Learning to Reject This article reviews the much-needed skill of learning to reject
… trends for improving the discrimination of three learning to reject tasks: failure, unknown, and …

… to two types of rejection, ambiguity and novelty rejection, which we … rejection and describe
the standard techniques for learning … learning with rejection relates to other machine learning …

… in the machine learning model, prediction with reject option (… review of the prediction with
the reject option in the context of … works in rejection classification in the machine learning field …

… To optimize model reliability, we propose the Reinforcement Learning from Knowledge
Feedback (RLKF) training framework based on RLHF. On the one hand, most publicly available …

… Learning to Reject and Active Learning both focus on the most uncertain regions of … Learning
we focus on uncertain samples at training time [16, 17], the objective of Learning to Reject …

… model) to learn the prediction errors of a classifier (base model) and reject instances with …
paper proposes a classifier rejection solution based on metalearning and novelty detection, …

… We propose to incorporate the reject option into our classification scheme by using a … to the
classical situation without the reject option. We emphasize that the rejection cost d should be …

… machine learning, namely modern variants of learning vector … the possibility of explicit reject
options for irregular samples. … with reject option, and we demonstrate the efficiency of reject …

… reliability and safety of machine learning systems. For instance, … In this survey, we first
present a unified framework called … uploaded by users, and reject such input instead of blindly …

… When examining academic rejection through the lens of effective learning, the vast literature
… accepted and rejected. Considering the limited literature pertaining to academic rejection, …