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Proof of Theorem 2.Forℓ∈[L], we omit the superscripts when these can be inferred from context

For ℓ∈[L], the result then follows by applying Theorem 1 to φn( ˆΘ,XB, Ψ ,ε) := ˜φn ( ˆΘ [:,ℓ],q(XB,Ψ,ε) ) = ˜φn ( ˆθ,y ) · 2009

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Inferring Change Points in Regression via Sample Weighting

stat.ME · 2026-04-13 · unverdicted · novelty 6.0

Weighted ERM encodes priors on change points through sample weights to obtain asymptotic characterizations of estimator performance in high-dimensional GLMs, enabling posterior inference over change points.

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  • Inferring Change Points in Regression via Sample Weighting stat.ME · 2026-04-13 · unverdicted · none · ref 2

    Weighted ERM encodes priors on change points through sample weights to obtain asymptotic characterizations of estimator performance in high-dimensional GLMs, enabling posterior inference over change points.