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Learning topic models — Provably and efficiently

Publication ,  Journal Article
Arora, S; Ge, R; Halpern, Y; Mimno, D; Moitra, A; Sontag, D; Wu, Y; Zhu, M
Published in: Communications of the ACM
April 1, 2018

Duke Scholars

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Published In

Communications of the ACM

DOI

EISSN

1557-7317

ISSN

0001-0782

Publication Date

April 1, 2018

Volume

61

Issue

4

Start / End Page

85 / 93

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences
 

Citation

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Arora, S., Ge, R., Halpern, Y., Mimno, D., Moitra, A., Sontag, D., … Zhu, M. (2018). Learning topic models — Provably and efficiently. Communications of the ACM, 61(4), 85–93. https://doi.org/10.1145/3186262
Arora, S., R. Ge, Y. Halpern, D. Mimno, A. Moitra, D. Sontag, Y. Wu, and M. Zhu. “Learning topic models — Provably and efficiently.” Communications of the ACM 61, no. 4 (April 1, 2018): 85–93. https://doi.org/10.1145/3186262.
Arora S, Ge R, Halpern Y, Mimno D, Moitra A, Sontag D, et al. Learning topic models — Provably and efficiently. Communications of the ACM. 2018 Apr 1;61(4):85–93.
Arora, S., et al. “Learning topic models — Provably and efficiently.” Communications of the ACM, vol. 61, no. 4, Apr. 2018, pp. 85–93. Scopus, doi:10.1145/3186262.
Arora S, Ge R, Halpern Y, Mimno D, Moitra A, Sontag D, Wu Y, Zhu M. Learning topic models — Provably and efficiently. Communications of the ACM. 2018 Apr 1;61(4):85–93.

Published In

Communications of the ACM

DOI

EISSN

1557-7317

ISSN

0001-0782

Publication Date

April 1, 2018

Volume

61

Issue

4

Start / End Page

85 / 93

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences