Philipp Kranen
RESEARCH SDE 2
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Publications
- Philipp Kranen, Marwan Hassani, and Thomas Seidl, BT* - An Advanced Algorithm for Anytime Classification, in Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece, 2012
- Anca Maria Ivanescu, Philipp Kranen, and Thomas Seidl, Hinging Hyperplane Models for Multiple Predicted Variables, in Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece, 2012
- Philipp Kranen, Ira Assent, Corinna Baldauf, and Thomas Seidl, The ClusTree: Indexing Micro-Clusters for Anytime Stream Mining, in Knowledge and Information Systems Journal (Springer KAIS), Volume 29, Issue 2, Springer, London, 2011
- Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, and Bernhard Pfahringer, An Effective Evaluation Measure for Clustering on Evolving Data Streams, in Proc. of the 17th ACM Conference on Knowledge Discovery and Data Mining (SIGKDD 2011), San Diego, CA, USA, ACM, New York, NY, USA, 2011
- Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, and Thomas Seidl, MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering, in Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis, Journal of Machine Learning Research, 2010
- Philipp Kranen, Ralph Krieger, Stefan Denker, and Thomas Seidl, Bulk loading Hierarchical Mixture Models for Efficient Stream Classification, in Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), Hyderabad, India. Springer LNAI, Springer, Heidelberg, Germany, 2010
- Philipp Kranen, Ira Assent, Corinna Baldauf, and Thomas Seidl, Self-Adaptive Anytime Stream Clustering, in Proc. IEEE International Conference on Data Mining (ICDM 2009), Miami, USA, IEEE Computer Society, Washington,USA, 2009
- Thomas Seidl, Ira Assent, Philipp Kranen, Ralph Krieger, and Jennifer Herrmann, Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams, in Proc. 12th International Conference on Extending Database Technology (EDBT/ICDT 2009), Saint-Petersburg, Russia., ACM, New York, NY, USA, 2009
- Philipp Kranen and Thomas Seidl, Harnessing the Strengths of Anytime Algorithms for Constant Data Streams, in Data Mining and Knowledge Discovery Journal (Springer DMKD), Special Issue on Selected Papers from ECML PKDD 2009, Vol. 19, No. 2,, Springer, Netherlands, 2009
- Marc Wichterich, Ira Assent, Philipp Kranen, and Thomas Seidl, Efficient EMD-based Similarity Search in Multimedia Databases via Flexible Dimensionality Reduction, in Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2008), Vancouver, BC, Canada., ACM, New York, NY, USA, 2008