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New Stabilized Higher-Order Influence Functions Detailed in arXiv Paper

By PulseAugur Editorial · [2 sources] ·

This paper introduces a new stabilized higher-order influence function estimator designed to improve the practical application of statistical estimation techniques. The proposed method aims to overcome the numerical instability and computational challenges associated with previous higher-order estimators, particularly those involving nonparametric density estimation or inverting large-dimensional matrices. The authors provide theoretical guarantees for their new class of estimators, suggesting they offer similar statistical performance to existing methods but with enhanced stability. AI

IMPACT This research contributes to the theoretical underpinnings of statistical estimation, potentially impacting future AI model development and analysis.

RANK_REASON The item is an academic paper published on arXiv detailing statistical theory. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New Stabilized Higher-Order Influence Functions Detailed in arXiv Paper

COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Na Liu, Chang Li, Yujia Gu, Lin Liu ·

    Stabilized Higher-Order Influence Functions: Statistical Theory of a Class of Bilinear Forms

    arXiv:2607.04743v1 Announce Type: cross Abstract: Higher-order influence functions, introduced in a series of articles (Robins et al., 2008, 2009a; van der Vaart, 2014; Robins et al., 2016, 2023; Liu et al., 2017), are a unified framework for constructing rate-optimal point estim…

  2. arXiv stat.ML TIER_1 English(EN) · Lin Liu ·

    Stabilized Higher-Order Influence Functions: Statistical Theory of a Class of Bilinear Forms

    Higher-order influence functions, introduced in a series of articles (Robins et al., 2008, 2009a; van der Vaart, 2014; Robins et al., 2016, 2023; Liu et al., 2017), are a unified framework for constructing rate-optimal point estimates of a class of statistical functionals, under …

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