Fabio Nikolay

Fabio Nikolay

Research Interests

  • Big Data
  • Convex Optimization

Short Bio

Fabio received his M.Sc. in Information and Communication Engineering from Technical University Darmstadt in June 2014. His Master Thesis was entitled „Convex Optimization-Based Beamforming for Multi-Group Multicasting with Statistical Channel State Information“. In July 2014 he joined the Communication Systems Group where he is now working towards his Ph.D..


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Gruppiere nach: Publikationsjahr | Typ des Eintrags | Keine Gruppierung
Anzahl der Einträge: 4.

Nikolay, Fabio (2019):
Graph Learning Methods for Genetic Interaction Networks.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00009634,

Nikolay, Fabio ; Pesavento, Marius (2017):
Learning Directed-Acyclic-Graphs from Multiple Genomic Data Sources.
In: Proceedings of the 25th European Signal Processing Conference, S. 1877-1881,
Kos Island, Greece, 25th European Signal Processing Conference, Kos Island, Greece, 28.08.17-02.09.17, DOI: 10.23919/EUSIPCO.2017.8081535,

Nikolay, Fabio ; Pesavento, Marius ; Kritikos, George ; Typas, Nassos (2017):
Learning directed acyclic graphs from large-scale genomics data.
In: EURASIP Journal on Bioinformatics and Systems Biology, 2017 (10), Springer Open, ISSN 1687-4153,
DOI: 10.1186/s13637-017-0063-3,

Nikolay, Fabio ; Pesavento, Marius (2016):
Learning directed-acyclic-graphs from large-scale double-knockout experimients.
In: Proceedings of the 2016 European Signal Processing Conference, S. 46-50,
Budapest, Hungary, The 24th European Signal Processing Conference (EUSIPCO 2016), Budapest, Hungary, 29.08.-02.09.2016, [Konferenzveröffentlichung]

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