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New algorithm improves hypothesis selection with weighted medians

Researchers have developed a new algorithm for hypothesis selection that improves upon existing methods. This algorithm uses weighted medians and requires fewer samples and less time to achieve a near-optimal approximation factor. It specifically reduces the dependence on the failure probability from polynomial to logarithmic, addressing a question posed by previous work. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing a new algorithm. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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New algorithm improves hypothesis selection with weighted medians

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The cluster contains a research paper published on arXiv detailing a new algorithm. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Liang-Yu Zou ·

    Hypothesis Selection via Weighted Medians

    arXiv:2610.20375v1 Announce Type: cross Abstract: Given $n$ distributions (hypotheses) $\mathcal H=\{H_1,\ldots,H_n\}$ and samples from an unknown target distribution $P$, proper hypothesis selection seeks a distribution whose total variation distance to $P$ is close to the best …