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New research details analytic function approximation by ReLU networks · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

A new research paper published on arXiv explores the approximation of analytic functions using ReLU neural networks. The study introduces a characterization that jointly considers network depth and width, moving beyond single-parameter analyses. The findings indicate that for analytic functions, network depth plays a more significant role than width, yielding approximation rates of \mathcal{O}\left(N^{-C L^{\tau}}\right). The paper details technical challenges and employs refined constructions for approximating power functions, multiplication, and polynomials. AI

IMPACT This research provides theoretical insights into the approximation capabilities of ReLU networks, potentially influencing future model architectures.

RANK_REASON The cluster contains an academic paper detailing theoretical advancements in neural network approximation.

Read on arXiv stat.ML →

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

New research details analytic function approximation by ReLU networks · 2 sources tracked

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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Yanming Lai, Defeng Sun, Yang Wang ·

    Approximation of Analytic Functions by ReLU Neural Networks with Adjustable Depth and Width

    arXiv:2607.10589v1 Announce Type: new Abstract: In contrast to most studies on neural network approximation theory that characterize results through a single parameter, such as the total number of network parameters, \cite{shen2020deep} pioneered the characterization of approxima…

  2. arXiv stat.ML TIER_1 English(EN) · Yang Wang ·

    Approximation of Analytic Functions by ReLU Neural Networks with Adjustable Depth and Width

    In contrast to most studies on neural network approximation theory that characterize results through a single parameter, such as the total number of network parameters, \cite{shen2020deep} pioneered the characterization of approximation rates as a joint function of the width para…

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