PulseAugur
EN
LIVE 19:24:44

Bias Estimation Bounds Tightened for List Replicable Algorithms

By PulseAugur Editorial · [1 sources] ·

Researchers have established tight bounds for bias estimation in list replicable algorithms, determining the optimal sample complexity for such methods. The study presents an improved algorithm that matches the derived lower bound up to polylogarithmic factors. For a list size of $d+1$, the optimal sample complexity is found to be $\widetilde{\Theta}\left(\frac{d^2}{\varepsilon^2}\right)$, and for a general list size $k$, it is $\widetilde{\Theta}\left(\frac{d^2}{\varepsilon^2\log k}\right)$. AI

IMPACT Establishes theoretical limits for bias estimation in algorithms, potentially impacting future algorithm design and analysis.

RANK_REASON The cluster contains an academic paper detailing theoretical research on algorithms and complexity. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

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

Bias Estimation Bounds Tightened for List Replicable Algorithms

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The cluster contains an academic paper detailing theoretical research on algorithms and complexity. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
4 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    The Price of List Replicability: Tight Bounds for Bias Estimation

    We study the sample complexity of list replicable algorithms for estimating the biases of $d$ coins. An algorithm is $(k,\varepsilon,δ)$-list replicable if for every bias vector $\mathbf{p}\in[0,1]^d$, there is a set of outputs $L_{\mathbf{p}}\subseteq \mathbb{R}^d$ of at most $k…

RELATED ENTITIES

RELATED TOPICS