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Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.

J. Thomas, A. Mayr, B. Bischl, M. Schmid, A. Smith, and B. Hofner. Statistics and Computing, 28 (3): 673-687 (2018)

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Dipl.-Ing. Thomas Kuestner

Scan time reduction in DWI of the pancreas using simultaneous multislice technique with different acceleration factors: how fast can we go?J. Taron, P. Martirosian, T. Küstner, M. Notohamiprodjo, J. Weiß, A. Othman, K. Nikolaou, and C. Schraml. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imagingH. Fayad, F. Odille, H. Schmidt, C. Würslin, T. Küstner, J. Felblinger, and D. Visvikis. Physics in medicine and biology, 60 (6): 2529-46 (March 2015)In-vivo MR-derived non-rigid motion correction of simultaneously acquired PETT. Küstner, C. Würslin, S. Gatidis, P. Martirosian, N. Schwenzer, B. Yang, and H. Schmidt. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, (June 2015)

Thomas Maier

Other publications of authors with the same name

compboost: Modular Framework for Component-Wise Boosting.D. Schalk, J. Thomas, and B. Bischl. J. Open Source Software, 3 (30): 967 (2018)Multi-Objective Automatic Machine Learning with AutoxgboostMC.F. Pfisterer, S. Coors, J. Thomas, and B. Bischl. CoRR, (2019)Corrigendum to "Probing for Sparse and Fast Variable Selection with Model-Based Boosting".J. Thomas, T. Hepp, A. Mayr, and B. Bischl. Comp. Math. Methods in Medicine, (2018)An Open Source AutoML Benchmark.P. Gijsbers, E. LeDell, J. Thomas, S. Poirier, B. Bischl, and J. Vanschoren. CoRR, (2019)Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning.J. Goschenhofer, F. Pfister, K. Yuksel, B. Bischl, U. Fietzek, and J. Thomas. CoRR, (2019)FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking.M. Rietzler, F. Geiselhart, J. Thomas, and E. Rukzio. EICS, page 73-84. ACM, (2016)Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.J. Thomas, A. Mayr, B. Bischl, M. Schmid, A. Smith, and B. Hofner. Statistics and Computing, 28 (3): 673-687 (2018)Automatic Exploration of Machine Learning Experiments on OpenML.D. Kühn, P. Probst, J. Thomas, and B. Bischl. CoRR, (2018)mlr Tutorial.J. Schiffner, B. Bischl, M. Lang, J. Richter, Z. Jones, P. Probst, F. Pfisterer, M. Gallo, D. Kirchhoff, T. Kühn and 2 other author(s). CoRR, (2016)Deep Semi-supervised Learning for Time Series Classification.J. Goschenhofer, R. Hvingelby, D. Rügamer, J. Thomas, M. Wagner, and B. Bischl. ICMLA, page 422-428. IEEE, (2021)

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Disambiguation of "Thomas, Janek"

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Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.

Please choose a person to relate this publication to

Dipl.-Ing. Thomas Kuestner

Thomas Maier

Thomas Maier

Thomas Maier

Thomas Maier

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Thomas, Janek"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.

Please choose a person to relate this publication to

Dipl.-Ing. Thomas Kuestner

Thomas Maier

Thomas Maier

Thomas Maier

Thomas Maier

Other publications of authors with the same name

Disambiguation

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URL
DOI
BibTeX
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Chicago
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Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.