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pro vyhledávání: '"Sutton David"'
Autor:
Kamalaruban, Parameswaran, Pi, Yulu, Burrell, Stuart, Drage, Eleanor, Skalski, Piotr, Wong, Jason, Sutton, David
Ensuring fairness in transaction fraud detection models is vital due to the potential harms and legal implications of biased decision-making. Despite extensive research on algorithmic fairness, there is a notable gap in the study of bias in fraud det
Externí odkaz:
http://arxiv.org/abs/2409.04373
Autor:
Perez, Iker, Wong, Jason, Skalski, Piotr, Burrell, Stuart, Mortier, Richard, McAuley, Derek, Sutton, David
Global financial crime activity is driving demand for machine learning solutions in fraud prevention. However, prevention systems are commonly serviced to financial institutions in isolation, and few provisions exist for data sharing due to fears of
Externí odkaz:
http://arxiv.org/abs/2401.02450
Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences
Publikováno v:
4th ACM International Conference on AI in Finance (ICAIF '23), November 27-29, 2023, Brooklyn, NY, USA
Machine learning models underpin many modern financial systems for use cases such as fraud detection and churn prediction. Most are based on supervised learning with hand-engineered features, which relies heavily on the availability of labelled data.
Externí odkaz:
http://arxiv.org/abs/2401.01641