Predicting user routines with masked dilated convolutions-Reference-Cited by-同舟云学术

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Predicting user routines with masked dilated convolutions

Published:2019-09-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 13th ACM Conference on Recommender Systems
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Author:

Wang Renzhong¹,Yankov Dragomir¹,Evans Michael R.²,Palanisamy Senthil¹,Arora Siddhartha¹,Wu Wei¹

Affiliation:

1. Microsoft

2. Microsoft, London, UK

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3298689.3347025

Reference16 articles.

1. Learning and user adaptation in location forecasting

2. Shaojie Bai J Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. (03 2018). Shaojie Bai J Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. (03 2018).

3. Derya Birant and Alp Kut. 2007. ST-DBSCAN: An Algorithm for Clustering Spatial-temporal Data. Data Knowl. Eng. 60 (01 2007) 208--221. 10.1016/j.datak.2006.01.013 Derya Birant and Alp Kut. 2007. ST-DBSCAN: An Algorithm for Clustering Spatial-temporal Data. Data Knowl. Eng . 60 (01 2007) 208--221. 10.1016/j.datak.2006.01.013

4. DeepMove

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