Bing Hu

According to our database, Bing Hu authored at least 19 papers between 2011 and 2017.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2017

Generalizing DTW to the multi-dimensional case requires an adaptive approach.

Mohammad Shokoohi-Yekta, Bing Hu, Hongxia Jin, Jun Wang, Eamonn J. Keogh

Data Min. Knowl. Discov., 2017

2016

Classification of streaming time series under more realistic assumptions.

Bing Hu, Yanping Chen, Eamonn J. Keogh

Data Min. Knowl. Discov., 2016

2015

Establishing the provenance of historical manuscripts with a novel distance measure.

Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh

Pattern Anal. Appl., 2015

A general framework for never-ending learning from time series streams.

Yanping Chen, Yuan Hao, Thanawin Rakthanmanon, Jesin Zakaria, Bing Hu, Eamonn J. Keogh

Data Min. Knowl. Discov., 2015

Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Data Min. Knowl. Discov., 2015

Discovery of Meaningful Rules in Time Series.

Mohammad Shokoohi-Yekta, Yanping Chen, Bilson J. L. Campana, Bing Hu, Jesin Zakaria, Eamonn J. Keogh

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

PinPlace: associate semantic meanings with indoor locations without active fingerprinting.

Xuan Bao, Bin Liu, Bo Tang, Bing Hu, Deguang Kong, Hongxia Jin

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2015

Protecting Your Children from Inappropriate Content in Mobile Apps: An Automatic Maturity Rating Framework.

Bing Hu, Bin Liu, Neil Zhenqiang Gong, Deguang Kong, Hongxia Jin

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2014

Connect the dots by understanding user status and transitions.

Xuan Bao, Yilin Shen, Neil Zhenqiang Gong, Hongxia Jin, Bing Hu

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2014

2013

Mining Time Series Data: Moving from Toy Problems to Realistic Deployments.

Bing Hu

PhD thesis, 2013

Time Series Classification under More Realistic Assumptions.

Bing Hu, Yanping Chen, Eamonn J. Keogh

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Towards never-ending learning from time series streams.

Yuan Hao, Yanping Chen, Jesin Zakaria, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

DTW-D: time series semi-supervised learning from a single example.

Yanping Chen, Bing Hu, Eamonn J. Keogh, Gustavo E. A. P. A. Batista

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Minimum Description Length Technique for Semi-Supervised Time Series Classification.

Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the Integration of Reusable Systems [extended versions of the best papers which were presented at IEEE International Conference on Information Reuse and Integration and IEEE International Workshop on Formal Methods Integration, 2013

Towards a minimum description length based stopping criterion for semi-supervised time series classification.

Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the IEEE 14th International Conference on Information Reuse & Integration, 2013

Classification of Multi-dimensional Streaming Time Series by Weighting Each Classifier's Track Record.

Bing Hu, Yanping Chen, Jesin Zakaria, Liudmila Ulanova, Eamonn J. Keogh

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Image Mining of Historical Manuscripts to Establish Provenance.

Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

2011

Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011