This thesis investigates how fairness is addressed within machine learning pipelines and proposes a framework for adversarial fairness testing through a human-in-the-loop approach. Although several fairness metrics and mitigation techniques have been proposed,…
This dissertation examines the use of artificial intelligence and machine learning in public employment services. Using comprehensive administrative labour market data, it investigates three key dimensions of algorithm-based occupational recommendations: predi…
s systèmes d’apprentissage automatique (AA), y compris les modèles classiques, les réseaux de neurones profonds (DNN) et les grands modèles de langage (LLMs), sont de plus en plus déployés dans des domaines à enjeux élevés tels que la santé, le recrutement, la…
Introduction Machine learning systems have increasingly taken control of making high-stake decisions about people’s lives. This can include who advances in a hiring pipeline, who is released before trial, or whose face a security camera flag. The reason behind…
Modern machine learning (ML) systems are increasingly required to operate in dynamic environments, where models must adapt to new information, remove obsolete or sensitive knowledge, and satisfy fairness and safety requirements. This thesis addresses these cha…
Intelligence artificielle digne de confiance grâce à l'apprentissage fédéré équitable et respectueux de la vie privée L'augmentation massive du volume de données disponibles a transformé l'informatique moderne, contribuant à l'essor de l'apprentissage automati…
Since their discovery in 2007, fast radio bursts (FRBs) have become a major focus of radio astronomy research because they enable researchers to probe the intergalactic medium beyond the Milky Way. Finding more FRBs will enable better understanding of the loca…
Quantum Machine Learning (QML):An emerging research area that integrates principles of quantum computing with machine learning algorithms to enhance computational efficiency, scalability, and learning capability for complex data-driven problems. Cloud-Based Qu…
Περίληψη Η εξατομικευμένη ιατρική επιδιώκει την προσαρμογή της πρόληψης, της διάγνωσης και της θεραπείας στα ιδιαίτερα χαρακτηριστικά κάθε ασθενούς, αξιοποιώντας δεδομένα από πολλαπλές πηγές, όπως το γονιδίωμα, οι εικόνες ιατρικής απεικόνισης, τα ηλεκτρονικά μ…
In recent years, we have observed a new revolution in computer science, driven by the increasing availability of computational power and data. This historic event has seen the capillary diffusion of what is commonly known as artificial intelligence (AI). In pa…
Quantum machine learning (QML) promises new representational and computational capabilities, yet practical deployment on near-term hardware is hampered by resource overheads, depth constraints, and fragile trainability. This thesis advances resource-aware QML…
This dissertation is presented in partial fulfillment of the requirements for Ph.D. degree in the Graduate School of Politecnico di Torino (ScuDo).La scrittura scientifica è notoriamente fredda, austera, priva di emozioni.Qualsiasi risultato ottenuto da un esp…
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