Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations

The development of new classification and regression algorithms based on empirical risk minimization (ERM) over deep neural network hypothesis classes, coined deep learning, revolutionized the area of artificial intelligence, machine learning, and data analysis. In particular, these methods have bee...

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Vydané v:	arXiv.org
Hlavní autori:	Berner, Julius, Grohs, Philipp, Jentzen, Arnulf
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 11.11.2020
Predmet:	Accuracy Algorithms Approximation Artificial intelligence Artificial neural networks Computer simulation Data analysis Drift Economic models Empirical analysis Error analysis Hypotheses Machine learning Mathematical models Neural networks Optimization Partial differential equations Regression analysis Scaling Statistical analysis
ISSN:	2331-8422
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