A federated learning approach to smart advertising

Συγγραφείς: Seyghaly, Rasool

Συνεισφορές: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: García Almiñana, Jordi, Masip Bruin, Xavier

Πηγή: TDX (Tesis Doctorals en Xarxa)

Θεματικοί όροι: Federated Learning (FL), Edge Computing, Smart Advertising, Privacy-Preserving Machine Learning, Personalized Ads, Whale Optimization Algorithm (WOA), Meta-Heuristic Aggregation, User Engagement, Click-Through Rate (CTR), Scalability in AI Systems, Indoor Positioning Systems, Real-Time Data Processing, Model Verification and Validation, GDPR & CCPA Compliance, Formal Verification in AI Systems, Àrees temàtiques de la UPC::Informàtica, 004 - Informàtica

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: http://hdl.handle.net/10803/694786
https://dx.doi.org/10.5821/dissertation-2117-433346

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Περιγραφή αρχείου: print

Σύνδεσμος πρόσβασης: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-55482
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