Hoang Anh Dau

According to our database, Hoang Anh Dau authored at least 16 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of two.

2020

The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code.

Yan Zhu, Shaghayegh Gharghabi, Diego Furtado Silva, Hoang Anh Dau, Chin-Chia Michael Yeh, Nader Shakibay Senobari, Abdulaziz Almaslukh, Kaveh Kamgar, Zachary Zimmerman, Gareth J. Funning, Abdullah Mueen, Eamonn J. Keogh

Data Min. Knowl. Discov., 2020

2019

Towards More Accurate Time Series Data Mining by Constraining Model's Flexibility.

Hoang Anh Dau

PhD thesis, 2019

The UCR time series archive.

Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh

IEEE CAA J. Autom. Sinica, 2019

Online Amnestic DTW to allow Real-Time Golden Batch Monitoring.

Chin-Chia Michael Yeh, Yan Zhu, Hoang Anh Dau, Amirali Darvishzadeh, Mikhail Noskov, Eamonn J. Keogh

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models.

Diego Romeres, Devesh K. Jha, William Yerazunis, Daniel Nikovski, Hoang Anh Dau

Proceedings of the 17th European Control Conference, 2019

2018

Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile.

Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh

Data Min. Knowl. Discov., 2018

Optimizing dynamic time warping's window width for time series data mining applications.

Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh

Data Min. Knowl. Discov., 2018

The UEA multivariate time series classification archive, 2018.

Anthony J. Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, Eamonn J. Keogh

CoRR, 2018

Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables.

Emil Laftchiev, Xinmaio Sun, Hoang Anh Dau, Daniel Nikovski

Proceedings of the 29th International Workshop on Principles of Diagnosis co-located with 10th IFAC Symposium on Fault Detection, 2018

Generalized Dynamic Time Warping: Unleashing the Warping Power Hidden in Point-Wise Distances.

Rodica Neamtu, Ramoza Ahsan, Elke A. Rundensteiner, Gábor N. Sárközy, Eamonn J. Keogh, Hoang Anh Dau, Cuong Nguyen, Charles Lovering

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017

Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery.

Hoang Anh Dau, Eamonn J. Keogh

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Generating Synthetic Time Series to Augment Sparse Datasets.

Germain Forestier, François Petitjean, Hoang Anh Dau, Geoffrey I. Webb, Eamonn J. Keogh

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series.

Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy.

Nurjahan Begum, Liudmila Ulanova, Hoang Anh Dau, Jun Wang, Eamonn J. Keogh

CoRR, 2016

Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets.

Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Semi-Supervision Dramatically Improves Time Series Clustering under Dynamic Time Warping.

Hoang Anh Dau, Nurjahan Begum, Eamonn J. Keogh

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016