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Matthias Schmid
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2020 – today
- 2024
- [i5]Qilun Zhu, Matthias Schmid, Robert Prucka, Ashley Boncimino, Chris Paredis:
Control Informed Design of the IAC Autonomous Racecar for Operation at the Dynamic Envelope. CoRR abs/2407.17737 (2024) - [i4]David Köhler, David Rügamer, Matthias Schmid:
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects. CoRR abs/2407.18650 (2024) - 2023
- [j28]Nikolai Spuck
, Matthias Schmid
Flexible tree-structured regression models for discrete event times. Stat. Comput. 33(1): 20 (2023) - 2022
- [b1]Matthias Schmid:
Towards Storing 3D Model Graphs in Relational Databases. University of Passau, Germany, 2022 - [j27]Thomas Augustin, Helmut Küchenhoff, Matthias Schmid
Nachruf Hans Schneeweiß. AStA Wirtschafts und Sozialstatistisches Arch. 16(2): 149-154 (2022) - [j26]Andrea Bommert
Benchmark of filter methods for feature selection in high-dimensional gene expression survival data. Briefings Bioinform. 23(1) (2022) - [i3]Saeed Maleki, Adhiti Raman, Yang Cheng, John L. Crassidis, Matthias Schmid:
Optimal Pose Estimation and Covariance Analysis with Simultaneous Localization and Mapping Applications. CoRR abs/2210.11697 (2022) - [i2]Saeed Maleki, John L. Crassidis, Yang Cheng, Matthias Schmid:
Error-Covariance Analysis of Monocular Pose Estimation Using Total Least Squares. CoRR abs/2210.12157 (2022) - 2021
- [j25]Shekoufeh Gorgi Zadeh
Bias in Cross-Entropy-Based Training of Deep Survival Networks. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 3126-3137 (2021) - [i1]Saeed Maleki, John L. Crassidis, Yang Cheng, Matthias Schmid:
Total Least Squares for Optimal Pose Estimation. CoRR abs/2106.11522 (2021) - 2020
- [j24]Matthias Schmid
Discrete-time survival forests with Hellinger distance decision trees. Data Min. Knowl. Discov. 34(3): 812-832 (2020) - [c11]Moreen Heine, Matthias Schmid:
Methods and tools in the early stages of legislation. ICEGOV 2020: 799-802 - [c10]Ayman Mohamed
A Low Noise CMOS Sensor Frontend for a TMR-based Biosensing Platform. IEEE SENSORS 2020: 1-4
2010 – 2019
- 2019
- [j23]Moritz Berger
A classification tree approach for the modeling of competing risks in discrete time. Adv. Data Anal. Classif. 13(4): 965-990 (2019) - [j22]Matthias Schmid
Proceedings of Reisensburg 2016-2017. Comput. Stat. 34(3): 943-944 (2019) - [j21]Thomas Welchowski
Sparse kernel deep stacking networks. Comput. Stat. 34(3): 993-1014 (2019) - [j20]Moritz Berger
Tree-structured modelling of varying coefficients. Stat. Comput. 29(2): 217-229 (2019) - [c9]Matthias Schmid:
An Approach to Efficiently Storing Property Graphs in Relational Databases. Grundlagen von Datenbanken 2019: 56-61 - [c8]Matthias Schmid:
On efficiently storing huge property graphs in relational database management systems. iiWAS 2019: 344-352 - 2018
- [j19]Hans A. Kestler
Proceedings of Reisensburg 2014-2015. Comput. Stat. 33(3): 1125-1126 (2018) - [j18]Janek Thomas
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates. Stat. Comput. 28(3): 673-687 (2018) - 2017
- [j17]Georg Stricker
GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis. Bioinform. 33(15): 2258-2265 (2017) - 2016
- [j16]Thomas Welchowski
A framework for parameter estimation and model selection in kernel deep stacking networks. Artif. Intell. Medicine 70: 31-40 (2016) - [j15]Florian Schmid, Matthias Schmid
GiANT: gene set uncertainty in enrichment analysis. Bioinform. 32(12): 1891-1894 (2016) - [j14]Andreas Mayr
Boosting the discriminatory power of sparse survival models via optimization of the concordance index and stability selection. BMC Bioinform. 17: 288 (2016) - [j13]Leonie Weinhold
A statistical model for the analysis of beta values in DNA methylation studies. BMC Bioinform. 17: 480:1-480:11 (2016) - [j12]Matthias Schmid
On the use of Harrell's C for clinical risk prediction via random survival forests. Expert Syst. Appl. 63: 450-459 (2016) - [c7]Aniketh Kalur, Kavyashree Shivakumar, Matthias Schmid, John L. Crassidis:
Adaptive control for spacecraft formation flying with solar radiation pressure and reduction of secular drift. ACC 2016: 5830-5835 - 2015
- [j11]Matthias Schmid
On the validity of time-dependent AUC estimators. Briefings Bioinform. 16(1): 153-168 (2015) - 2014
- [j10]Simone Wahl, Nora Fenske, Sonja Zeilinger
On the potential of models for location and scale for genome-wide DNA methylation data. BMC Bioinform. 15: 232 (2014) - [j9]Harald Binder
Proceedings of Reisensburg 2011. Comput. Stat. 29(1): 1-2 (2014) - [j8]Benjamin Hofner
Model-based boosting in R: a hands-on tutorial using the R package mboost. Comput. Stat. 29(1): 3-35 (2014) - [j7]Ludwig Lausser, Florian Schmid, Matthias Schmid
Unlabeling data can improve classification accuracy. Pattern Recognit. Lett. 37: 15-23 (2014) - 2013
- [j6]Harald Binder
Proceedings of Reisensburg 2010. Comput. Stat. 28(1): 1-3 (2013) - [c6]Dominik Klein, Thomas Zinner, Kathrin Borchert, Stanislav Lange, Vlad Singeorzan, Matthias Schmid:
Evaluation of Video Quality Monitoring Based on Pre-computed Frame Distortions. EUNICE 2013: 100-111 - 2012
- [c5]Michael Duelli, Sebastian Meier, David P. Wagner, Thomas Zinner, Matthias Schmid, Marco Hoffmann, Wolfgang Kiess:
Experimental Demonstration of Network Virtualization and Resource Flexibility in the COMCON Project. TRIDENTCOM 2012: 114-129 - 2011
- [j5]Werner Adler
Ensemble classification of paired data. Comput. Stat. Data Anal. 55(5): 1933-1941 (2011) - 2010
- [j4]Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner:
Model-based Boosting 2.0. J. Mach. Learn. Res. 11: 2109-2113 (2010) - [j3]Matthias Schmid
Estimation and regularization techniques for regression models with multidimensional prediction functions. Stat. Comput. 20(2): 139-150 (2010) - [c4]Marc M. Muntzinger, Michael Aeberhard, Sebastian Zuther, Mirko Mählisch, Matthias Schmid, Jürgen Dickmann, Klaus Dietmayer:
Reliable automotive pre-crash system with out-of-sequence measurement processing. Intelligent Vehicles Symposium 2010: 1022-1027
2000 – 2009
- 2008
- [j2]Matthias Schmid
Flexible boosting of accelerated failure time models. BMC Bioinform. 9 (2008) - [j1]Matthias Schmid
Boosting additive models using component-wise P-Splines. Comput. Stat. Data Anal. 53(2): 298-311 (2008) - 2003
- [c3]Marc Fetscherin, Matthias Schmid:
Comparing the usage of digital rights management systems in the music, film, and print industry. ICEC 2003: 316-325 - [c2]Michael Menth, Matthias Schmid, Herbert Heiss, Thomas Reim:
MEDF - A Simple Scheduling Algorithm for Two Real-Time Transport Service Classes with Application in the UTRAN. INFOCOM 2003: 1116-1122 - [c1]Marc Fetscherin, Matthias Schmid:
The application of digital rights management systems in the music industry - an empirical investigation. WEDELMUSIC 2003: 115-121
Coauthor Index
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last updated on 2024-11-05 20:57 CET by the dblp team
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