A regret-minimization algorithm for online conformal prediction under adversarial semi-bandit feedback achieves long-run coverage guarantees while controlling prediction set size.
At each round t∈[T] , the learner chooses an arm πt from a given set Π, where we refer to the problem as K-armed bandit problem when |Π|=K
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization
A regret-minimization algorithm for online conformal prediction under adversarial semi-bandit feedback achieves long-run coverage guarantees while controlling prediction set size.