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Michael Fauss
Michael Fauss
Postdoctoral Research Fellow, Princeton University
Verified email at princeton.edu - Homepage
Title
Cited by
Cited by
Year
Old bands, new tracks—Revisiting the band model for robust hypothesis testing
M Fauß, AM Zoubir
IEEE Transactions on signal Processing 64 (22), 5875-5886, 2016
282016
A linear programming approach to sequential hypothesis testing
M Fauß, AM Zoubir
Sequential Analysis 34 (2), 235-263, 2015
222015
Minimax robust landmine detection using forward-looking ground-penetrating radar
AD Pambudi, M Fauß, F Ahmad, AM Zoubir
IEEE Transactions on Geoscience and Remote Sensing 58 (7), 5032-5041, 2020
202020
Minimax robust detection: Classic results and recent advances
M Fauß, AM Zoubir, HV Poor
IEEE Transactions on signal Processing 69, 2252-2283, 2021
192021
MMSE bounds for additive noise channels under Kullback–Leibler divergence constraints on the input distribution
A Dytso, M Fauß, AM Zoubir, HV Poor
IEEE Transactions on Signal Processing 67 (24), 6352-6367, 2019
182019
On optimizing the conditional value-at-risk of a maximum cost for risk-averse safety analysis
MP Chapman, M Fauß, KM Smith
IEEE Transactions on Automatic Control 68 (6), 3720-3727, 2022
142022
Robust sequential testing of multiple hypotheses in distributed sensor networks
MR Leonard, M Stiefel, M Fauß, AM Zoubir
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
142018
Minimax optimal sequential hypothesis tests for Markov processes
M Fauss, AM Zoubir, HV Poor
The Annals of Statistics 48 (5), 2599-2621, 2020
132020
Bayesian sequential joint detection and estimation
D Reinhard, M Fauß, AM Zoubir
Sequential Analysis 37 (4), 530-570, 2018
132018
Block sparsity-based DOA estimation with sensor gain and phase uncertainties
H Huang, M Fauß, AM Zoubir
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
112019
The vector Poisson channel: On the linearity of the conditional mean estimator
A Dytso, M Fauß, HV Poor
IEEE Transactions on Signal Processing 68, 5894-5903, 2020
102020
An approach to joint sequential detection and estimation with distributional uncertainties
D Reinhard, M Fauß, AM Zoubir
2016 24th European Signal Processing Conference (EUSIPCO), 2201-2205, 2016
102016
Bayesian risk with Bregman loss: A Cramér–Rao type bound and linear estimation
A Dytso, M Fauß, HV Poor
IEEE Transactions on Information Theory 68 (3), 1985-2000, 2021
92021
Bayesian sequential joint signal detection and signal-to-noise ratio estimation
D Reinhard, M Fauß, AM Zoubir
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
92019
In a one-bit rush: Low-latency wireless spectrum monitoring with binary sensor arrays
MS Stein, M Fauß
2018 IEEE Statistical Signal Processing Workshop (SSP), 223-227, 2018
92018
Exploiting sparsity for robust sensor network localization in mixed LOS/NLOS environments
D Jin, F Yin, M Fauß, M Muma, AM Zoubir
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
82020
Sequential joint detection and estimation with an application to joint symbol decoding and noise power estimation
D Reinhard, M Fauß, AM Zoubir
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
82020
Distributed joint detection and estimation: A sequential approach
D Reinhard, M Fauß, AM Zoubir
2020 54th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2020
82020
CVaR-based safety analysis in the infinite time horizon setting
C Wei, M Fauß, MP Chapman
2022 American Control Conference (ACC), 2863-2870, 2022
72022
A variational interpretation of the Cramér–Rao bound
M Fauß, A Dytso, HV Poor
Signal Processing 182, 107917, 2021
72021
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