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On large-scale probabilistic and statistical data analysis

. Dortmund University, Germany, (2018)base-search.net (ftunivdortmund:oai:eldorado.tu-dortmund.de:2003/37116).

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On large-scale probabilistic and statistical data analysis. Dortmund University, Germany, (2018)base-search.net (ftunivdortmund:oai:eldorado.tu-dortmund.de:2003/37116).Scalable Learning of Item Response Theory Models., , and . CoRR, (2024)Probabilistic Smallest Enclosing Ball in High Dimensions via Subgradient Sampling., and . SoCG, volume 129 of LIPIcs, page 47:1-47:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2019)Coresets and Sketches for Regression Problems on DataStreams and Distributed Data.. Mach. Learn. under Resour. Constraints Vol. 1 (1), De Gruyter, (2022)Bayesian Analysis for Dimensionality and Complexity Reduction., , and . Mach. Learn. under Resour. Constraints Vol. 3 (3), De Gruyter, (2022)A Framework for Bayesian Optimization in Embedded Subspaces., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4752-4761. PMLR, (2019)Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves., , and . NeurIPS, page 12807-12817. (2019)Core Dependency Networks., , and . AAAI, page 3820-3827. AAAI Press, (2018)Coresets-Methods and History: A Theoreticians Design Pattern for Approximation and Streaming Algorithms., and . Künstliche Intell., 32 (1): 37-53 (2018)Streaming statistical models via Merge & Reduce., , , and . Int. J. Data Sci. Anal., 10 (4): 331-347 (2020)