Home ›
Entities
› academia
› A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions
A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions
Research article (Zeitschrift für angewandte Mathematik und Physik, 2022) · cited 13× · AI/ML
A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions
Summary
A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions is a scholarly article[1].
Key Facts
A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-proof-of-convergence-for-stochastic-gradient-descent-in-the-training-of-artificial-neural-networks-with-relu-activatio
MLA“A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-proof-of-convergence-for-stochastic-gradient-descent-in-the-training-of-artificial-neural-networks-with-relu-activatio.
BibTeX@misc{4ortxyz_a-proof-of-convergence-for-stochastic-gradient-descent-in-the-training-of-artificial-neural-networks-with-relu-activatio_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions}}, year = {2026}, url = {https://4ort.xyz/entity/a-proof-of-convergence-for-stochastic-gradient-descent-in-the-training-of-artificial-neural-networks-with-relu-activatio}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions — https://4ort.xyz/entity/a-proof-of-convergence-for-stochastic-gradient-descent-in-the-training-of-artificial-neural-networks-with-relu-activatio (retrieved 2026-05-24)