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New framework links betting tests and Blackwell approachability

By PulseAugur Editorial · [1 sources] ·

This paper introduces a novel framework connecting betting-based sequential tests with Blackwell approachability through support-function residuals. It establishes an exact pathwise identity relating the distance to a target set with the sum of prediction errors and regret. The research formulates a controlled stochastic experiment where adaptive nulls lead to sublinear regret and exponential wealth under persistent mean separation, with applications to bounded means, kernel MMD, and heterogeneous data sources. AI

IMPACT Introduces theoretical advancements in sequential testing and statistical inference, potentially impacting future AI research in decision-making and hypothesis testing.

RANK_REASON The cluster contains an academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework links betting tests and Blackwell approachability

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The cluster contains an academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jinze Zhao ·

    From Approachability Residuals to Anytime-Valid Evidence: The Online Convex Geometry of Testing by Betting

    arXiv:2608.09450v1 Announce Type: new Abstract: Betting-based sequential tests and Blackwell approachability are linked by a rate-explicit reduction through support-function residuals. For a compact convex target $S$ and vector observations $r_t$, an OCO learner selects a predict…

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