Unified GLR-based stopping rules with new self-normalized time-uniform deviation inequalities deliver finite-sample precision guarantees for contextual learning under unknown variances in linear settings.
Operations Research, 71(1), 148–183
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Unified Precision-Guaranteed Stopping Rules for Contextual Learning
Unified GLR-based stopping rules with new self-normalized time-uniform deviation inequalities deliver finite-sample precision guarantees for contextual learning under unknown variances in linear settings.