Partially Generative Neural Networks for Gang Crime Classification with Partial Information-Reference-Cited by-同舟云学术

Partially Generative Neural Networks for Gang Crime Classification with Partial Information

Published:2018-12-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society
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Author:

Seo Sungyong¹,Chan Hau²,Brantingham P. Jeffrey³,Leap Jorja³,Vayanos Phebe¹,Tambe Milind¹,Liu Yan¹

Affiliation:

1. University of Southern California, Los Angeles, CA, USA

2. University of Nebraska-Lincoln, Lincoln, NE, USA

3. University of California, Los Angeles, Los Angeles, CA, USA

Funder

National Science Foundation

MINERVA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3278721.3278758

Reference28 articles.

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2. THE ECOLOGY OF GANG TERRITORIAL BOUNDARIES*

3. Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag and Yan Liu. 2016. Recurrent neural networks for multivariate time series with missing values. arXiv preprint arXiv:1606.01865 (2016). Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag and Yan Liu. 2016. Recurrent neural networks for multivariate time series with missing values. arXiv preprint arXiv:1606.01865 (2016).

4. Validating Self-Nomination in Gang Research: Assessing Differences in Gang Embeddedness Across Non-, Current, and Former Gang Members

5. Federal Bureau of Investigation. 2015. Crime in the United States. (2015). Federal Bureau of Investigation. 2015. Crime in the United States. (2015).

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