Correlated Time Series Forecasting using Multi-Task Deep Neural Networks

Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan, Chenjuan Guo, Bin Yang

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)
Original languageEnglish
Title of host publicationCIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management
EditorsNorman Paton, Selcuk Candan, Haixun Wang, James Allan, Rakesh Agrawal, Alexandros Labrinidis, Alfredo Cuzzocrea, Mohammed Zaki, Divesh Srivastava, Andrei Broder, Assaf Schuster
Number of pages4
PublisherAssociation for Computing Machinery
Publication date17 Oct 2018
Pages1527-1530
ISBN (Electronic)978-1-4503-6014-2
DOIs
Publication statusPublished - 17 Oct 2018
Event27th ACM International Conference on Information and Knowledge Management - Torino, Italy
Duration: 22 Oct 201826 Oct 2018
http://www.cikm2018.units.it/

Conference

Conference27th ACM International Conference on Information and Knowledge Management
CountryItaly
CityTorino
Period22/10/201826/10/2018
Internet address

Fingerprint

Time series
Recurrent neural networks
Neural networks
Analog to digital conversion
Deep neural networks
Sensors
Experiments

Keywords

  • Correlated time series
  • Deep learning
  • Multi-Task Learning

Cite this

Cirstea, R-G., Micu, D-V., Muresan, G-M., Guo, C., & Yang, B. (2018). Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. In N. Paton, S. Candan, H. Wang, J. Allan, R. Agrawal, A. Labrinidis, A. Cuzzocrea, M. Zaki, D. Srivastava, A. Broder, ... A. Schuster (Eds.), CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management (pp. 1527-1530). Association for Computing Machinery. https://doi.org/10.1145/3269206.3269310
Cirstea, Razvan-Gabriel ; Micu, Darius-Valer ; Muresan, Gabriel-Marcel ; Guo, Chenjuan ; Yang, Bin. / Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management. editor / Norman Paton ; Selcuk Candan ; Haixun Wang ; James Allan ; Rakesh Agrawal ; Alexandros Labrinidis ; Alfredo Cuzzocrea ; Mohammed Zaki ; Divesh Srivastava ; Andrei Broder ; Assaf Schuster. Association for Computing Machinery, 2018. pp. 1527-1530
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Cirstea, R-G, Micu, D-V, Muresan, G-M, Guo, C & Yang, B 2018, Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. in N Paton, S Candan, H Wang, J Allan, R Agrawal, A Labrinidis, A Cuzzocrea, M Zaki, D Srivastava, A Broder & A Schuster (eds), CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, pp. 1527-1530, Torino, Italy, 22/10/2018. https://doi.org/10.1145/3269206.3269310

Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. / Cirstea, Razvan-Gabriel; Micu, Darius-Valer; Muresan, Gabriel-Marcel; Guo, Chenjuan; Yang, Bin.

CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management. ed. / Norman Paton; Selcuk Candan; Haixun Wang; James Allan; Rakesh Agrawal; Alexandros Labrinidis; Alfredo Cuzzocrea; Mohammed Zaki; Divesh Srivastava; Andrei Broder; Assaf Schuster. Association for Computing Machinery, 2018. p. 1527-1530.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AU - Micu, Darius-Valer

AU - Muresan, Gabriel-Marcel

AU - Guo, Chenjuan

AU - Yang, Bin

PY - 2018/10/17

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KW - Correlated time series

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A2 - Paton, Norman

A2 - Candan, Selcuk

A2 - Wang, Haixun

A2 - Allan, James

A2 - Agrawal, Rakesh

A2 - Labrinidis, Alexandros

A2 - Cuzzocrea, Alfredo

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A2 - Srivastava, Divesh

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Cirstea R-G, Micu D-V, Muresan G-M, Guo C, Yang B. Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. In Paton N, Candan S, Wang H, Allan J, Agrawal R, Labrinidis A, Cuzzocrea A, Zaki M, Srivastava D, Broder A, Schuster A, editors, CIKM '18 Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery. 2018. p. 1527-1530 https://doi.org/10.1145/3269206.3269310