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AFA-BANDIT: Provably Near-Optimal Online Multi-Feature Classification Under Budget Constraints
Active Feature Acquisition (AFA) is a classification problem in which an agent decides which costly features to acquire before predicting each sample's label. Unlike batch AFA, which trains a fixed policy and classifier offline on fully observed data, online AFA updates its predictor from revealed l
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