no code implementations • 3 Oct 2022 • Clemens Karner, Vladimir Kazeev, Philipp Christian Petersen
We study the training of deep neural networks by gradient descent where floating-point arithmetic is used to compute the gradients.
3 code implementations • 25 Feb 2018 • Markus Bachmayr, Vladimir Kazeev
Folding grid value vectors of size $2^L$ into $L$th order tensors of mode sizes $2\times \cdots\times 2$, combined with low-rank representation in the tensor train format, has been shown to lead to highly efficient approximations for various classes of functions.
Numerical Analysis 15A69, 35J25, 65N12, 65N30, 65N55, 65F08, 65F35, 65Y20
