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math.ST2026
Learning of deep neural network regression estimates using gradient descent with pruning
Michael Kohler, Vincent Molinero Römer, Adam Krzyżak
Estimation of a regression function from independent and identically distributed data is considered. The error with integration with respect to the design variable is used as…
math.ST2026
Estimation of a regression function from dependent data by over-parametrized deep neural networks learned by gradient descent
Michael Kohler, Adam Krzyżak, Vincent Molinero Römer
Estimation of a regression function from exponentially -mixing data is considered. The error with integration with respect to the design is used as the error criterion. De…