Development of New Machine Learning Models Based on Gaussian Processes. Applications to Remote Sensing and Astrophysics

  1. Morales Álvarez, Pablo
unter der Leitung von:
  1. Rafael Molina Soriano Doktorvater
  2. Aggelos K. Katsaggelos Doktorvater/Doktormutter

Universität der Verteidigung: Universidad de Granada

Fecha de defensa: 05 von Oktober von 2020

Gericht:
  1. Javier Mateos Delgado Präsident
  2. Mari Luz García Martínez Sekretär/in
  3. Sandra Morales Martínez Vocal
  4. Juan Gabriel Serra Pérez Vocal
  5. Valeriana Naranjo Ornedo Vocal
Fachbereiche:
  1. CIENCIAS DE LA COMPUTACIÓN E INTELIGENCIA ARTIFICIAL

Art: Dissertation

Zusammenfassung

In this PhD thesis we have developed different machine learning models based on Gaussian Processes. Different settings (regression, classification and crowdsourcing) are considered, and various application fields (specially remote sensing and astrophysics, but also threat detection and sentiment analysis) are targeted. The main global conclusion of this PhD thesis is the versatility of Gaussian Processes to model different scenarios (regression, classification, crowdsourcing) and target various applications (remote sensing, security, astrophysics), either as the central algorithm to perform the task at hand (Chapters 2-7) or as an auxiliary tool to be integrated within a larger model (Chapter 8)