Foto von Francesca Diedolo

M.Sc. Francesca Diedolo

Technische Universität München

Lehrstuhl für Nachrichtentechnik (Prof. Kramer)

Postadresse

Postal:
Theresienstr. 90
80333 München

Biografie

  • Seit Februar 2021 wissenschaftliche Mitarbeiterin am Lehrstuhl für Nachrichtentechnik der TUM
  • M.Sc. in  Communications Engineering an der TUM, 2018-2020
  • B.Sc. in Elektro- und Informationstechnik an der Università degli Studi di Padova, 2015-2018

Lehre

Machine Learning for Communications(WS 21/22, WS 22/23, WS 23/24)

Wireless Communications Laboratory (SS22)

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Probabilistic Principal Component Analysis

Beschreibung

Principal component analysis (PCA) [1] is a famous technique for feature extraction and dimensionality reduction. Despite its widespread use and effectiveness, PCA is constrained by its linear nature.

Probabilistic PCA [2] improves upon classical PCA by linking it with maximum likelihood estimation based on a probability density model of the observed data.

The task of the student is to read about probabilistic PCA. The  student should understand the underlying theoretical concepts of the algorithm, its application spectrum, as well as its limitations.

 

[1] https://arxiv.org/pdf/1404.1100.pdf

[2] https://www.cs.columbia.edu/~blei/seminar/2020-representation/readings/TippingBishop1999.pdf

Voraussetzungen

Information Theory, Linear Algebra

Betreuer:

Publikationen

2024

  • Plabst, D.; Prinz, T.; Diedolo, F.; Wiegart, T.; Boecherer, G.; Hanik, N.; Kramer, G.: Neural network equalizers and successive interference cancellation for bandlimited channels with a nonlinearity. Submitted to IEEE Trans. Commun., 2024 mehr… BibTeX
  • Plabst, D.; Prinz, T.; Diedolo, F.; Wiegart, T.; Böcherer, G.; Hanik, N.; Kramer, G.: Neural network equalizers and successive interference cancellation for bandlimited channels with a nonlinearity. IEEE International Symposium on Information Theory, 2024 mehr… BibTeX

2022

  • Diedolo, F.; Böcherer, G.; Schädler M.; Calabrò S.: Nonlinear Equalization for Optical Communications Based on Entropy-Regularized Mean Square Error. European Conference on Optical Communication (ECOC), 2022 mehr… BibTeX
  • Schädler, M.; Böcherer, G.; Diedolo, F.; Calabrò, S.: Nonlinear Component Equalization: A Comparison of Deep Neural Networks and Volterra Series. European Conference on Optical Communication (ECOC), 2022 mehr… BibTeX

2021

  • Böcherer, G.; Diedolo, F.; Pittala, F.: Label Extension for 32QAM: The Extra Bit for a Better FEC Performance-Complexity Tradeoff. 2020 European Conference on Optical Communications (ECOC), IEEE, 2021 mehr… BibTeX Volltext ( DOI )