Tung Kieu

Orcid: 0000-0002-7696-1444

Affiliations:

Aalborg Universitet, Denmark
University of Science, Vietnam National University, Ho Chi Minh City, Vietnam (former)

According to our database¹, Tung Kieu authored at least 20 papers between 2017 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2023

LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation.

[BibT_eX]

[DOI]

Proc. ACM Manag. Data, 2023

WAVER: Writing-style Agnostic Text-Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge.

[BibT_eX]

[DOI]

CoRR, 2023

LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation - Extended Version.

[BibT_eX]

[DOI]

CoRR, 2023

2022

A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis.

[BibT_eX]

[DOI]

CoRR, 2022

Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting-Full Version.

[BibT_eX]

[DOI]

Razvan-Gabriel Cirstea

CoRR, 2022

Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection - Extended Version.

[BibT_eX]

[DOI]

CoRR, 2022

Towards Spatio-Temporal Aware Traffic Time Series Forecasting-Full Version.

[BibT_eX]

[DOI]

Razvan-Gabriel Cirstea

CoRR, 2022

Outlier Detection for Streaming Task Assignment in Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting.

[BibT_eX]

[DOI]

Razvan-Gabriel Cirstea

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders.

[BibT_eX]

[DOI]

Tung Kieu

Bin Yang

Chenjuan Guo

Razvan-Gabriel Cirstea

Yan Zhao

Yale Song

Christian S. Jensen

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Towards Spatio- Temporal Aware Traffic Time Series Forecasting.

[BibT_eX]

[DOI]

Razvan-Gabriel Cirstea

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles - Extended Version.

[BibT_eX]

[DOI]

CoRR, 2021

EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting.

[BibT_eX]

[DOI]

Razvan-Gabriel Cirstea

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2020

Multiple Electric Energy Consumption Forecasting Using a Cluster-Based Strategy for Transfer Learning in Smart Building.

[BibT_eX]

[DOI]

Sensors, 2020

2019

Outlier Detection for Time Series with Recurrent Autoencoder Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Outlier Detection for Multidimensional Time Series Using Deep Neural Networks.

[BibT_eX]

[DOI]

Tung Kieu

Bin Yang

Christian S. Jensen

Proceedings of the 19th IEEE International Conference on Mobile Data Management, 2018

Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories.

[BibT_eX]

[DOI]

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Mining top-k co-occurrence items with sequential pattern.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2017

Tung Kieu

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