Konferenzveröffentlichung

Machkour, Jasin ; Muma, Michael ; Palomar, Daniel P. (2023)
The Informed Elastic Net for Fast Grouped Variable Selection and FDR Control in Genomics Research.
9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. Herradura, Costa Rica (10.12. - 13.12.2023)
doi: 10.1109/CAMSAP58249.2023.10403489
Konferenzveröffentlichung, Bibliographie

Machkour, Jasin ; Muma, Michael ; Palomar, Daniel P. (2023)
False Discovery Rate Control for Fast Screening of Large-Scale Genomics Biobanks.
22nd IEEE Statistical Signal Processing Workshop. Hanoi, Vietnam (02.07. - 05.07.2023)
doi: 10.1109/SSP53291.2023.10207957
Konferenzveröffentlichung, Bibliographie

Machkour, Jasin ; Muma, Michael ; Palomar, Daniel P. (2022)
False Discovery Rate Control for Grouped Variable Selection in High-Dimensional Linear Models Using the T-Knock Filter.
30th European Signal Processing Conference. Belgrade, Serbia (29.08.2022-02.09.2022)
doi: 10.23919/EUSIPCO55093.2022.9909883
Konferenzveröffentlichung, Bibliographie

Yang, Yang ; Mengyi, Zhang ; Pesavento, Marius ; Palomar, Daniel P. (2014)
An online parallel algorithm for spectrum sensing in cognitive radio networks.
48th Asilomar Conference on Signals, Systems and Computers. Pacific Grove (02.11.2014-05.11.2014)
Konferenzveröffentlichung, Bibliographie

Report

Machkour, Jasin ; Palomar, Daniel P. ; Muma, Michael (2024)
FDR-Controlled Portfolio Optimization for Sparse Financial Index Tracking.
doi: 10.48550/arXiv.2401.15139
Report, Bibliographie

Machkour, Jasin ; Muma, Michael ; Palomar, Daniel P. (2024)
High-Dimensional False Discovery Rate Control for Dependent Variables.
doi: 10.48550/arXiv.2401.15796
Report, Bibliographie

Machkour, Jasin ; Breloy, Arnaud ; Muma, Michael ; Palomar, Daniel P. ; Pascal, Frédéric (2024)
Sparse PCA with False Discovery Rate Controlled Variable Selection.
doi: 10.48550/arXiv.2401.08375
Report, Bibliographie

Machkour, Jasin ; Muma, Michael ; Palomar, Daniel P. (2022)
The Terminating-Random Experiments Selector: Fast High-Dimensional Variable Selection with False Discovery Rate Control.
doi: 10.48550/arXiv.2110.06048
Report, Bibliographie