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Dekobild im Seitenkopf ISMLL
 
People: Nicolas Schilling, Dipl. Math.
Office hour:
C040 Spl, upon request
Phone, Fax, Email:
Phone: +49 5121/ 883-40376
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

Publications:

  • Mohsan Jameel, Nicolas Schilling, Lars Schmidt-Thieme (2018):
    Towards Distributed Pairwise Ranking using Implicit Feedback, in The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), pp. 973-976 .
  • Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme (2017):
    Finding Hierarchy of Topics from Twitter Data, in Proceedings of Knowledge Discovery, Data Mining and Machine Learning (KDML 2017), Rostock, Germany.
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2017 ):
    Automatic Frankensteining: Creating Complex Ensembles Autonomously, in Proceedings of the 2017 SIAM International Conference on Data Mining (SDM 17) , SIAM , pp. 741-749 . PDF
  • Martin Wistuba, Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Bank Card Usage Prediction Exploiting Geolocation Information, in , Riva del Garda, Italy. ECML-PKDD 2016 Discovery Challenge Award: Best System of the Bank Card Usage Analysis Challenge. PDF
  • Nghia Duong-Trung, Nicolas Schilling, Lucas Rego Drumond, Lars Schmidt-Thieme (2016):
    Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream, in Proceedings of Knowledge Discovery, Data Mining and Machine Learning (KDML 2016), Potsdam, Germany.
  • Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Near Real-time Geolocation Prediction in Twitter Streams via Matrix Factorization Based Regression, in Proceedings of ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, USA.
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'16), Riva del Garda, Italy. PDF
  • Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2016):
    Scalable Hyperparameter Optimization with Products of Gaussian Process Experts, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'16), Riva del Garda, Italy. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Hyperparameter Optimization Machines, in Proceedings of IEEE International Conference on Data Science and Advanced Analytics (DSAA'16), Montreal, Canada. PDF
  • 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
  • Nghia Duong-Trung, Nicolas Schilling, Lucas Rego Drumond, Lars Schmidt-Thieme (2015):
    An Effective Approach for Geolocation Prediction in Twitter Streams Using Clustering Based Discretization, in Proceedings of the 39th European Conference on Data Analysis, KIT Scientific Publishing, Colchester, United Kingdom.
  • Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme (2015):
    Joint Model Choice and Hyperparameter Optimization with Factorized Multilayer Perceptrons, in 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2015), Vietri sul Mare, Italy. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Sequential Model-free Hyperparameter Tuning, in Proceedings of IEEE International Conference on Data Mining (ICDM'15), Atlantic City, NJ, USA. Acceptance Rate: 18.2% (147 out of 807). PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Learning Hyperparameter Optimization Initializations, in Proceedings of IEEE International Conference on Data Science and Advanced Analytics (DSAA'15), Paris, France. PDF
  • Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme (2015):
    Hyperparameter Optimization with Factorized Multilayer Perceptrons, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'15), Porto, Portugal. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Hyperparameter Search Space Pruning - A New Component for Sequential Model-Based Hyperparameter Optimization, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'15), Porto, Portugal. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Learning Data Set Similarities for Hyperparameter Optimization Initializations, in Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (MetaSel@ECML'15), Porto, Portugal. 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
  • Nicolas Schilling, Andre Busche, Simone Miller, Michael Jungheim, Martin Ptok, Lars Schmidt-Thieme (2014):
    Event Prediction in Pharyngeal High-Resolution Manometry , to appear in Proceedings of the European Conference on Data Analysis, ECDA 2013, Springer, Luxemburg. PDF