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New research decouples single-instance learning rates from direct-sum rates

By PulseAugur Editorial · [1 sources] ·

A new research paper by Hanneke, Moran, and Waknine explores the relationship between agnostic PAC learning curves and direct sums in machine learning. The study demonstrates that the learning rate of a single instance does not dictate the direct-sum rate. Specifically, the paper analyzes two classes of functions, F and G, both exhibiting an agnostic learning curve of order n^{-1/2}, to illustrate this principle. AI

IMPACT This research contributes to the theoretical understanding of machine learning algorithms, potentially informing future algorithm design.

RANK_REASON The item is an academic paper published on arXiv discussing theoretical machine learning concepts. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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

New research decouples single-instance learning rates from direct-sum rates

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The item is an academic paper published on arXiv discussing theoretical machine learning concepts. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mihir More, Aritra Das, Debayan Gupta ·

    A Rate Separation for Agnostic Direct Sums

    arXiv:2608.06951v1 Announce Type: new Abstract: Hanneke, Moran, and Waknine \cite{HannekeMoranWaknine2024} asked how the agnostic PAC learning curve of the direct sum $C^r$ depends on the single-instance learning curve $\epsagn(n\mid C)$ and on $r$. We show that the single-instan…

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