wir bieten...
Dekobild im Seitenkopf ISMLL
 
People: Dr. Josif Grabocka
Office hour:
C35 Spl, upon request

Contact:
Phone:+49 5121/ 883-40368
Fax:+49 5121 / 883-40361
e-mail:

Postal address:
Information Systems and Machine Learning Lab
Universitätsplatz 1
University of Hildesheim
31141 Hildesheim
Germany

Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany

Highlights:

Publications:

Journal papers:

  • Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Latent Time-Series Motifs, ACM Transactions on Knowledge Discovery from Data, TKDD
  • Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2015):
    Fast Classification of Univariate and Multivariate Time series Through Shapelets Discovery, Journal of Knowledge and Information Systems, 5-year impact factor 2.02
  • Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2014):
    Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials, IEEE Transactions on Knowledge and Data Engineering, 5-year impact factor 2.87
  • Josif Grabocka, Lars Schmidt-Thieme (2014):
    Invariant Time-Series Factorization, Journal of Data Mining and Knowledge Discovery, Impact Factor 2.77
  • Josif Grabocka, Lars Schmidt-Thieme (2014):
    Learning Through Non-linearly Supervised Dimensionality Reduction, Springer Transactions on Large-Scale Data- and Knowledge-Centered Systems, LNCS

Peer-Reviewed Conference Papers:
  • Mit Shah, Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2016):
    Learning DTW-Shapelets for Time-Series Classification, in ACM IKDD Conference on Data Science. Best Paper Award. PDF
  • Josif Grabocka, Alexandros Dalkalitsis, Athanasios Lois, Evangelos Katsaros, Lars Schmidt-Thieme (2014):
    Realistic Optimal Policies for Energy-Efficient Train Driving, in Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, ITSC 2014. PDF
  • Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2014):
    Learning Time-Series Shapelets, in Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2014. Acceptance Rate: 14.6% (151 out of 1036). PDF
  • Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2014):
    Supervised Nonlinear Factorizations Excel In Semi-supervised Regression , in Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, Springer, LNCS, Tainan, Taiwan. PDF
  • Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme (2013):
    Supervised Dimensionality Reduction Via Nonlinear Target Estimation, in Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013 . PDF
  • Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2012):
    Efficient Classification of Long Time Series, in Proceedings of ICT Innovations Conference 2012, Advances in Intelligent Systems and Computing, Volume 207, pp 47-57, Springer, Berlin/Heidelberg . PDF
  • Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Invariant Time-Series Classification, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'12) , Bristol, United Kingdom. PDF
  • Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Classification of Sparse Time Series via Supervised Matrix Factorization, in Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI'12), Toronto, Canada. PDF





Locations of Site Visitors