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
APA
Chicago
ICMJE
MLA
NLM
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