Hugging Face Trending Papers
Anytime-valid simulation-based hypothesis testing
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arXiv Machine Learning
Oct 7
Anytime-valid simulation-based hypothesis testing
arXiv:2610. 08210v1 Announce Type: cross Abstract: For a given data distribution $(X_t)_{t \in \mathbb{N}} \sim Q$ i.
arXiv Machine Learning
Jun 16
Asymptotically Optimal Sequential Testing with Markovian Data
arXiv:2602. 17587v3 Announce Type: replace-cross Abstract: We study one-sided and $\alpha$-correct sequential hypothesis testing for data generated by an ergodic, finite-state Markov chain.
arXiv Machine Learning
Aug 18
On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
arXiv:2504. 19952v2 Announce Type: replace-cross Abstract: We present two general lower bounds for stopping times of sequential tests between arbitrary composite nulls $\mathcal P$ and alternatives $\mathcal Q$.
arXiv Machine Learning
Sep 24
Type-II Error Bounds for Test Supermartingales from Lower-Tail Hypotheses
arXiv:2609.27766v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingals, Ville's inequality provides anytime-valid type-I error guarantees for every significance level...
arXiv Machine Learning
Oct 19
Information-Geometric Blind Spots of Conformal Test Martingales
arXiv:2610. 23131v1 Announce Type: cross Abstract: Conformal test martingales (CTMs) are e-processes for sequentially testing exchangeability via p-values produced by a conformity function $A$.
arXiv Machine Learning
Jun 15
Testing For Distribution Shifts with Conditional Conformal Test Martingales
arXiv:2602. 13848v2 Announce Type: replace Abstract: We propose a sequential test for detecting arbitrary distribution shifts that allows conformal test martingales (CTMs) to work under a fixed, reference-conditional setting.