Bing Hu

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Eamonn KeoghDistinguished Professor of Computer Science, University of California - RiversideDirección de correo verificada de cs.ucr.edu
Yanping ChenUniversity of California, RiversideDirección de correo verificada de ucr.edu
Thanawin RakthanmanonDept. of Computer Engineering, Kasetsart University, ThailandDirección de correo verificada de ku.ac.th
Gustavo Enrique BatistaAssociate Professor, School of Computer Science and Engineering, University of New South WalesDirección de correo verificada de cse.unsw.edu.au
Abdullah MueenProfessor, Department of Computer Science, University of New MexicoDirección de correo verificada de cs.unm.edu
Nurjahan BegumUniversity of California, RiversideDirección de correo verificada de cs.ucr.edu
Yuan HaoPh.D Candidate of Computer Science and Engineering, University of California, RiversideDirección de correo verificada de cs.ucr.edu
Jesin ZakariaMicrosoftDirección de correo verificada de ucr.edu
Tony BagnallProfessor of Computer Science, University of SouthamptonDirección de correo verificada de uea.ac.uk
Scott EvansPrincipal Scientist Machine Learning, GE ResearchDirección de correo verificada de ge.com
Stefano LonardiProfessor of Computer Science, University of California, RiversideDirección de correo verificada de cs.ucr.edu
Deguang KongGoogleDirección de correo verificada de google.com
Liudmila UlanovaPhD in Computer Science, University of California, RiversideDirección de correo verificada de ucr.edu
Chotirat Ann RatanamahatanaAssociate Professor, Dept. of Computer Engineering, Chulalongkorn UniversityDirección de correo verificada de chula.ac.th

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Bing Hu

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Machine Learning Data Mining Statistics


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
The UCR Time Series Classification/Clustering Homepage E Keogh, Q Zhu, B Hu, H Y, X Xi, L Wei, CA Ratanamahatana	1337*	2011
Generalizing DTW to the multi-dimensional case requires an adaptive approach M Shokoohi-Yekta, B Hu, H Jin, J Wang, E Keogh Data mining and knowledge discovery 31, 1-31, 2017	340	2017
Time series classification under more realistic assumptions B Hu, Y Chen, E Keogh Proceedings of the 2013 SIAM international conference on data mining, 578-586, 2013	178	2013
DTW-D: Time Series Semi-Supervised Learning from a Single Example Y Chen, B Hu, E Keogh Knowledge Discovery and Data Mining (KDD), 2013, 2013	171	2013
Discovery of meaningful rules in time series M Shokoohi-Yekta, Y Chen, B Campana, B Hu, J Zakaria, E Keogh Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015	113	2015
Discovering the Intrinsic Cardinality and Dimensionality of Time Series using MDL B Hu, T Rakthanmanon, Y Hao, E Scott, E Keogh International Conference on Data Mining (ICDM), 2011	77	2011
A general framework for never-ending learning from time series streams Y Chen, Y Hao, T Rakthanmanon, J Zakaria, B Hu, E Keogh Data mining and knowledge discovery 29, 1622-1664, 2015	52	2015
Classification of Multi-Dimensional Streaming Time Series by Weighting each Classifier's Track Record B Hu, Y Chen, L Ulanova, E Keogh International Conference on Data Mining (ICDM), 2013, 2013	49	2013
Towards never-ending learning from time series streams Y Hao, Y Chen, J Zakaria, B Hu, T Rakthanmanon, E Keogh Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	43	2013
Classification of streaming time series under more realistic assumptions B Hu, Y Chen, E Keogh Data mining and knowledge discovery 30 (2), 403-437, 2016	41	2016
Multilevel-3D bit patterned magnetic media with 8 signal levels per nanocolumn N Amos, J Butler, B Lee, MH Shachar, B Hu, Y Tian, J Hong, D Garcia, ... PLoS One 7 (7), e40134, 2012	38	2012
Protecting your children from inappropriate content in mobile apps: An automatic maturity rating framework B Hu, B Liu, NZ Gong, D Kong, H Jin Proceedings of the 24th ACM International on Conference on Information and …, 2015	37	2015
Towards a minimum description length based stopping criterion for semi-supervised time series classification N Begum, B Hu, T Rakthanmanon, E Keogh 2013 IEEE 14th international conference on information reuse & integration …, 2013	30	2013
Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series B Hu, T Rakthanmanon, Y Hao, S Evans, S Lonardi, E Keogh Data Mining and Knowledge Discovery 29, 358-399, 2015	28	2015
Study of Co/Pd Multilayers as a Candidate Material for Next Generation Magnetic Media B Hu, N Amos, Y Tian, J Butler, D Litvinov, S Khizroev Journal of Applied Physics 109, 2010	27	2010
System and method for fault detection in an electrical device DR Garvey, SC Evans, B Hu US Patent 9,394,899, 2016	19	2016
Image Mining of Historical Manuscripts to Establish Provenance B Hu, T Rakthanmanon, B Campana, A Mueen, E Keogh SIAM International Conference on Data Mining (SDM), 2011	15	2011
Pinplace: associate semantic meanings with indoor locations without active fingerprinting X Bao, B Liu, B Tang, B Hu, D Kong, H Jin Proceedings of the 2015 ACM International Joint Conference on Pervasive and …, 2015	14	2015
Reconfigurable and non-volatile vertical magnetic logic gates J Butler, M Shachar, B Lee, D Garcia, B Hu, J Hong, N Amos, S Khizroev Journal of Applied Physics 115 (16), 2014	13	2014
HY, X. Xi, L. Wei, and CA Ratanamahatana,“The ucr time series classification/clustering homepage,” E Keogh, Q Zhu, B Hu	12	2011

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