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21 Publications


2009 | Dissertation | LibreCat-ID: 2911
M. R. Ackermann, Algorithms for the Bregman k-Median Problem. Universität Paderborn, 2009.
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2009 | Book Chapter | LibreCat-ID: 2995
M. R. Ackermann and J. Blömer, “Coresets and Approximate Clustering for Bregman Divergences,” in Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, Philadelphia, PA: Society for Industrial and Applied Mathematics, 2009, pp. 1088–1097.
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2010 | Book Chapter | LibreCat-ID: 2988
M. R. Ackermann and J. Blömer, “Bregman Clustering for Separable Instances,” in SWAT 2010, Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 212–223.
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2010 | Journal Article | LibreCat-ID: 2990
M. R. Ackermann, J. Blömer, and C. Sohler, “Clustering for Metric and Nonmetric Distance Measures,” ACM Trans. Algorithms, no. 4, pp. 59:1--59:26, 2010.
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2010 | Journal Article | LibreCat-ID: 2991
A. Krueger, V. Leutnant, R. Haeb-Umbach, M. Ackermann, and J. Blömer, “On the initialization of dynamic models for speech features,” Proc. of ITG Fachtagung Sprachkommunikation. ITG, Bochum, Germany, 2010.
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2011 | Conference Paper | LibreCat-ID: 2985
M. R. Ackermann, J. Blömer, and C. Scholz, “Hardness and Non-Approximability of Bregman Clustering Problems.” 2011.
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2012 | Conference Paper | LibreCat-ID: 2982
M. R. Ackermann, M. Märtens, C. Raupach, K. Swierkot, C. Lammersen, and C. Sohler, “StreamKM++: A clustering algorithm for data streams,” vol. 17. ACM, New York, NY, USA, 2012.
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2013 | Dissertation | LibreCat-ID: 2909
D. Kuntze, Practical algorithms for clustering and modeling large data sets - Analysis and improvements. Universität Paderborn, 2013.
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2014 | Mastersthesis | LibreCat-ID: 2900
S. Brauer, A Probabilistic Expectation Maximization Algorithm for Multivariate Laplacian Mixtures. 2014.
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2014 | Journal Article | LibreCat-ID: 2976
M. R. Ackermann, J. Blömer, D. Kuntze, and C. Sohler, “Analysis of Agglomerative Clustering,” Algorithmica, vol. 69, 2014.
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2014 | Conference Paper | LibreCat-ID: 2977
J. Blömer, K. Bujna, and D. Kuntze, “A Theoretical and Experimental Comparison of the EM and SEM Algorithm,” in 2014 22nd International Conference on Pattern Recognition, 2014.
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2016 | Preprint | LibreCat-ID: 2969 | OA
J. Blömer, S. Brauer, and K. Bujna, “Hard-Clustering with Gaussian Mixture Models.” Computing Research Repository, 2016.
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2016 | Book Chapter | LibreCat-ID: 2970
J. Blömer and K. Bujna, “Adaptive Seeding for Gaussian Mixture Models,” in Advances in Knowledge Discovery and Data Mining, Cham: Springer International Publishing, 2016, pp. 296–308.
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2016 | Conference Paper | LibreCat-ID: 2367
J. Blömer, S. Brauer, and K. Bujna, “A Theoretical Analysis of the Fuzzy K-Means Problem,” in 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, Spain, 2016, pp. 805–810.
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2017 | Dissertation | LibreCat-ID: 2908
K. Bujna, Soft Clustering Algorithms - Theoretical and Practical Improvements. Universität Paderborn, 2017.
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2017 | Book Chapter | LibreCat-ID: 2381
S. Brauer, “Complexity of Single-Swap Heuristics for Metric Facility Location and Related Problems,” in Lecture Notes in Computer Science, vol. 10236, D. Fotakis, A. Pagourtzis, and V. T. Paschos, Eds. Cham: Springer International Publishing, 2017, pp. 116–127.
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2018 | Conference Paper | LibreCat-ID: 4344
J. Blömer, S. Brauer, and K. Bujna, “Coresets for Fuzzy K-Means with Applications,” in 29th International Symposium on Algorithms and Computation  (ISAAC 2018), Jiaoxi, Yilan County, Taiwan, 2018, pp. 46:1--46:12.
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2019 | Journal Article | LibreCat-ID: 2916
S. Brauer, “Complexity of single-swap heuristics for metric facility location and related problems,” Theoretical Computer Science, vol. 754, pp. 88–106, 2019.
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2019 | Dissertation | LibreCat-ID: 13679
S. Brauer, Classification and Approximation of Geometric Location Problems. Paderborn, 2019.
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2020 | Journal Article | LibreCat-ID: 20888
J. Blömer, S. Brauer, and K. Bujna, “A Complexity Theoretical Study of Fuzzy K-Means,” ACM Transactions on Algorithms, vol. 16, no. 4, pp. 1–25, 2020.
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2020 | Journal Article | LibreCat-ID: 10790
J. Blömer, S. Brauer, K. Bujna, and D. Kuntze, “How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models,” Advances in Data Analysis and Classification, vol. 14, pp. 147–173, 2020.
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