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Research paper analyzes prior choices in high-dimensional shrinkage risk

A new research paper delves into the impact of prior choices on high-dimensional shrinkage risk, specifically examining the difference between priors that are flat on variance versus those flat on standard deviation. The study demonstrates that these distinct prior allocations near the zero-scale boundary lead to different shrinkage behaviors. Under a radial-power benchmark, priors flat on standard deviation show an asymptotic risk advantage near the origin and exhibit distinct behavior in critical regimes. AI

RANK_REASON Academic paper on statistical methodology. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv stat.ML →

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Research paper analyzes prior choices in high-dimensional shrinkage risk

COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Zhiheng You ·

    Variance or Standard Deviation? Shell Geometry and Global-Scale Priors in High-Dimensional Shrinkage

    We study how the choice of default prior for a common Gaussian scale affects high-dimensional shrinkage risk, highlighting the role played by high-dimensional geometry. Formally, we consider a high-dimensional setting in which the near-zero behavior of the common scale prior has …