Elizabeth Newman

Assistant Professor

slimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks


Journal article


Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto
SIAM Journal on Scientific Computing, vol. 44(4), 2022, pp. A2322-A2348


Code (Matlab) Code (Python)
Cite

Cite

APA   Click to copy
Newman, E., Chung, J., Chung, M., & Ruthotto, L. (2022). slimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks. SIAM Journal on Scientific Computing, 44(4), A2322–A2348. https://doi.org/10.1137/21M1452512


Chicago/Turabian   Click to copy
Newman, Elizabeth, Julianne Chung, Matthias Chung, and Lars Ruthotto. “SlimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks.” SIAM Journal on Scientific Computing 44, no. 4 (2022): A2322–A2348.


MLA   Click to copy
Newman, Elizabeth, et al. “SlimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks.” SIAM Journal on Scientific Computing, vol. 44, no. 4, 2022, pp. A2322–A2348, doi:10.1137/21M1452512.


BibTeX   Click to copy

@article{newman2022a,
  title = {slimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks},
  year = {2022},
  issue = {4},
  journal = {SIAM Journal on Scientific Computing},
  pages = {A2322-A2348},
  volume = {44},
  doi = {10.1137/21M1452512},
  author = {Newman, Elizabeth and Chung, Julianne and Chung, Matthias and Ruthotto, Lars}
}