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Michael Geilke

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2010 – 2019

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2018
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  - journals/datamine/GeilkeKF018
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Michael Geilke, Andreas Karwath, Eibe Frank, Stefan Kramer:
Online estimation of discrete, continuous, and conditional joint densities using classifier chains. Data Min. Knowl. Discov. 32(3): 561-603 (2018)
2017
[b1]
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Michael Geilke:
Online density estimates: a probabilistic condensed representation of data for knowledge discovery. Johannes Gutenberg University Mainz, Germany, 2017
[c7]
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  - conf/icbk/Geilke017
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Michael Geilke, Stefan Kramer:
Privacy-Preserving Pattern Mining on Online Density Estimates. ICBK 2017: 25-32
2016
[c6]
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  - conf/pkdd/GeilkeK016
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Michael Geilke, Andreas Karwath, Stefan Kramer:
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions. ECML/PKDD (1) 2016: 65-80
2015
[c5]
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Michael Geilke, Andreas Karwath, Stefan Kramer:
Modeling recurrent distributions in streams using possible worlds. DSAA 2015: 1-9
2014
[c4]
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  - conf/dsaa/GeilkeK014
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Michael Geilke, Andreas Karwath, Stefan Kramer:
A probabilistic condensed representation of data for stream mining. DSAA 2014: 297-303
2013
[c3]
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  - conf/icdm/GeilkeFKK13
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Michael Geilke, Eibe Frank, Andreas Karwath, Stefan Kramer:
Online Estimation of Discrete Densities. ICDM 2013: 191-200
2012
[c2]
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  - conf/lata/GeilkeZ12
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Michael Geilke, Sandra Zilles:
Polynomial-Time Algorithms for Learning Typed Pattern Languages. LATA 2012: 277-288
2011
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Michael Geilke, Sandra Zilles:
Learning Relational Patterns. ALT 2011: 84-98

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