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Michael W. Mahoney

32 papers hereh-index 388.8k citations82 works total

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

author position
  • middle author10
  • last author16

Across the 26 of 32 papers where every author was matched, so the position is known.

fields
  • cs.LG15
  • cs.CV6
  • cs.CL4
  • stat.ML4
  • cs.DC1
  • cs.DS1
same name
  • Michael W. Mahoney — 70 papers, h 68
  • Michael W. Mahoney — 20 papers, h 10
  • Michael W. Mahoney — 14 papers, h 9
  • Michael W. Mahoney — 12 papers
  • Michael W. Mahoney — 11 papers, h 7
  • Michael W. Mahoney — 10 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedContinuous-in-Depth Neural Networks

26 citations · 58 across the 9 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2023

A Three-regime Model of Network Pruning

Yefan Zhou, Yaoqing Yang, Arin Chang +1

Recent work has highlighted the complex influence training hyperparameters, e.g., the number of training epochs, can have on the prunability of machine learning models. Perhaps sur…

stat.ML2023★ 4 cited

When are ensembles really effective?

Ryan Theisen, Hyunsuk Kim, Yaoqing Yang +2

Ensembling has a long history in statistical data analysis, with many impactful applications. However, in many modern machine learning settings, the benefits of ensembling are less…

stat.ML2022★ 2 cited

Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows

Feynman Liang, Liam Hodgkinson, Michael W. Mahoney

While fat-tailed densities commonly arise as posterior and marginal distributions in robust models and scale mixtures, they present challenges when Gaussian-based variational infer…

stat.ML2020

Error Estimation for Sketched SVD via the Bootstrap

Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney

In order to compute fast approximations to the singular value decompositions (SVD) of very large matrices, randomized sketching algorithms have become a leading approach. However,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.