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cs.LG2025
FD4QC: Application of Classical and Quantum-Hybrid Machine Learning for Financial Fraud Detection A Technical Report
Matteo Cardaioli, Luca Marangoni, Giada Martini +5
The increasing complexity and volume of financial transactions pose significant challenges to traditional fraud detection systems. This technical report investigates and compares t…
cs.LG2025
Moshi Moshi? A Model Selection Hijacking Adversarial Attack
Riccardo Petrucci, Luca Pajola, Francesco Marchiori +2
Model selection is a fundamental task in Machine Learning~(ML), focusing on selecting the most suitable model from a pool of candidates by evaluating their performance on specific…