MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning.

Granziol D, Ru B, Zohren S, Dong X, Osborne M, Roberts S

DOI: 10.3390/e21060551
Published: 2019 May 31
Container: Entropy (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/e21060551,
  title = {MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning.},
  author = {Granziol D and Ru B and Zohren S and Dong X and Osborne M and Roberts S},
  year = {2019},
  journal = {Entropy (Basel, Switzerland)},
  doi = {10.3390/e21060551},
  url = {https://doi.org/10.3390/e21060551}
}

RIS

TY  - JOUR
TI  - MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning.
AU  - Granziol D
AU  - Ru B
AU  - Zohren S
AU  - Dong X
AU  - Osborne M
AU  - Roberts S
PY  - 2019
JO  - Entropy (Basel, Switzerland)
DO  - 10.3390/e21060551
UR  - https://doi.org/10.3390/e21060551
ER  -

APA

D, G., B, R., S, Z., X, D., M, O., & S, R. (2019). MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning.. Entropy (Basel, Switzerland). https://doi.org/10.3390/e21060551

Source records

pubmed · retrieved 2026-09-24T22:49:08.557Z