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Semper, Sebastian ; Römer, Florian; Hotz, Thomas; Del Galdo, Giovanni
Grid-free Direction-of-Arrival estimation with compressed sensing and arbitrary antenna arrays. - In: IEEE Xplore digital library. - New York, NY : IEEE, (2018), S. 3251-3255
https://doi.org/10.1109/ICASSP.2018.8462501
Semper, Sebastian ; Römer, Florian; Hotz, Thomas; Del Galdo, Giovanni
Sparsity order estimation from a single compressed observation vector. - In: IEEE transactions on signal processing : SP : a publication of the IEEE Signal Processing Society. - New York, NY : IEEE, Bd. 66 (2018), 15, S. 3958-3971
https://doi.org/10.1109/TSP.2018.2841867
Dietrich, Thomas ; Krug, Silvia; Hotz, Thomas; Zimmermann, Armin
Towards energy consumption prediction with safety margins for multicopter systems. - In: The ACM digital library. - New York, NY : ACM, (2017), S. 227-228
Fast abstract
https://doi.org/10.1145/3150928.3150964
Glock, Matthias ; Hotz, Thomas
Constructing universal, non-asymptotic confidence sets for intrinsic means on the circle. - In: Geometric science of information : third International Conference, GSI 2017, Paris, France, November 7-9, 2017 : proceedings. - Cham : Springer International Publishing, ISBN 978-3-319-68445-1, (2017), S. 477-485

https://doi.org/10.1007/978-3-319-68445-1_56
Zimmermann, Armin ; Hotz, Thomas; Canabal Lavista, Andrés
A hybrid multi-trajectory simulation algorithm for the performance evaluation of stochastic petri nets. - In: Quantitative evaluation of systems : 14th international conference, QEST 2017, Berlin, Germany, September 5-7, 2017 : proceedings. - Cham : Springer International Publishing, ISBN 978-3-319-66335-7, (2017), S. 107-122

https://doi.org/10.1007/978-3-319-66335-7_7
Vogel, Silvia
Random approximations in multiobjective optimization. - Ilmenau : Techn. Univ., Inst. für Mathematik. - Online-Ressource (PDF-Datei: 27 S., 304,7 KB). - (Preprint. - M14,12)

Often decision makers have to cope with a programming problem with unknown quantitities. Then they will estimate these quantities and solve the problem as it then appears - the 'approximate problem'. Thus there is a need to establish conditions which will ensure that the solutions to the approximate problem will come close to the solutions to the true problem in a suitable manner. Confidence sets, i.e. sets that cover the true sets with a given prescribed probability, provide useful quantitative information. In this paper we consider multiobjective problems and derive confidence sets for the sets of efficient points, weakly efficient points, and the corresponding solution sets. Besides the crucial convergence conditions for the objective and/or constraint functions, one approach for the derivation of confidence sets requires some knowledge about the true problem, which may be not available. Therefore also another method, called relaxation, is suggested. This approach works without any knowledge about the true problem. The results are applied to the Markowitz model of portfolio optimization.


http://www.db-thueringen.de/servlets/DocumentServlet?id=25361
Vogel, Silvia ; Schettler, Anne
A uniform concentration-of-measure inequality for multivariate kernel density estimators. - Ilmenau : Techn. Univ., Inst. für Mathematik. - Online-Ressource (PDF-Datei: 10 S., 264,6 KB). - (Preprint. - M13,09)
http://www.db-thueringen.de/servlets/DocumentServlet?id=22415
Sinotina, Tatiana ; Vogel, Silvia
Universal confidence sets for the mode of a regression function. - In: IMA journal of management mathematics. - Oxford : Univ. Press, ISSN 14716798, Bd. 23 (2012), 4, S. 309-323
http://dx.doi.org/10.1093/imaman/dps011
Vogel, Silvia
Universal confidence sets - estimation and relaxation. - Ilmenau : Techn. Univ., Inst. für Mathematik. - Online-Ressource (PDF-Datei: 14 S., 192,5 KB). - (Preprint. - M11,12)
http://www.db-thueringen.de/servlets/DocumentServlet?id=18490
Sinotina, Tatiana ; Vogel, Silvia
Universal confidence sets for the mode of a regression function. - Ilmenau : Techn. Univ., Inst. für Mathematik. - Online-Ressource (PDF-Datei: 17 S., 211 KB). - (Preprint. - M10,02)
http://www.db-thueringen.de/servlets/DocumentServlet?id=14876