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M. Hochstenbach

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.NA3
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20192021
most citedA Simple and Efficient Stochastic Rounding Method for Training Neural Networks in Low Precision

3 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

math.NA2021

A Generalized CUR decomposition for matrix pairs

Perfect Y. Gidisu, Michiel E. Hochstenbach

We propose a generalized CUR (GCUR) decomposition for matrix pairs (A,B). Given matrices A and B with the same number of columns, such a decomposition provides low-rank appr…

cs.LG2021★ 3 cited

A Simple and Efficient Stochastic Rounding Method for Training Neural Networks in Low Precision

Lu Xia, Martijn Anthonissen, Michiel Hochstenbach +1

Conventional stochastic rounding (CSR) is widely employed in the training of neural networks (NNs), showing promising training results even in low-precision computations. We introd…

math.NA2020★ 2 cited

Improved stochastic rounding

Lu Xia, Martijn Anthonissen, Michiel Hochstenbach +1

Due to the limited number of bits in floating-point or fixed-point arithmetic, rounding is a necessary step in many computations. Although rounding methods can be tailored for diff…

math.NA2019

A twin error gauge for Kaczmarz's iterations

Bart S. van Lith, Per Christian Hansen, Michiel E. Hochstenbach

We propose two new algebraic reconstruction techniques based on Kaczmarz's method that produce a regularized solution to noisy tomography problems. Tomography problems exhibit semi…

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