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Asymptotic properties of one-layer artificial neural networks with sparse connectivity
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DOI
- https://doi.org/10.1016/j.spl.2022.109698
Final published version
- Christian Hirsch
- Matthias Neumann, Ulm University ,
- Volker Schmidt, Ulm University
A law of large numbers for the empirical distribution of parameters of a one-layer artificial neural network with sparse connectivity is derived for a simultaneously increasing number of both, neurons and training iterations of the stochastic gradient descent.
| Original language | English |
|---|---|
| Article number | 109698 |
| Journal | Statistics & Probability Letters |
| Volume | 193 |
| ISSN | 0167-7152 |
| DOIs | |
| Publication status | Published - Feb 2023 |
Bibliographical note
Publisher Copyright:
© 2022 Elsevier B.V.
- Artificial neural network, Law of large numbers, Random network, Sparse connectivity, Stochastic gradient descent, Weak convergence
Research areas
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ID: 312883567