# Arora 2018: Learning topic models -- provably and efficiently

> Sanjeev Arora, Rong Ge, Yoni Halpern et al., 2018. 1 records on Mysteries Department cite it. Listed among the topic-model references in the…

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[Sources](https://mysteriesdept.com/sources)[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)Arora 2018

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# Learning topic models -- provably and efficiently

Sanjeev Arora, Rong Ge, Yoni Halpern et al., 2018. _Communications of the ACM_.

A Communications of the ACM overview of anchor-word algorithms, which learn topic models with provable guarantees and run quickly in practice.

**Voynich Manuscript** Articledoi: **[10.1145/3186262](https://doi.org/10.1145/3186262)** Checked against the original0

## What it's used for here

Listed among the topic-model references in the inductive-methods survey.

## Cited by on this site 1 record

[1 methods surveys]

Inductive methods

SRC

## Cite it

```
Arora, S., Ge, R., Halpern, Y., Mimno, D., Moitra, A., Sontag, D., Wu, Y., & Zhu, M. (2018). Learning topic models -- provably and efficiently. Communications of the ACM. https://doi.org/10.1145/3186262
```

[Read it free at doi.org](https://doi.org/10.1145/3186262)

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