Adaptive Machine Learning for Credit Card Fraud Detection

By Andrea Dal Pozzolo, Gianluca Bontempi. 2015

104 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Sergey Levine
2. Rishabh Agarwal
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Ruslan Salakhutdinov
6. Trevor Darrell
7. Nicholas Frosst
8. Dacheng Tao

Citations in the corpus

• Neural Additive Models: Interpretable Machine Learning with Neural Nets (2020, background): “tient’s fever or blood pressure) would be. The shape plots do, however, tell us exactly how the model makes its predictions. 3.1.3 Credit Fraud: Financial Fraud Detection This is a large dataset [Dal Pozzolo, 2015] containing 284,807 transactions made by European credit cardholders where the task is”
• Sequence classification for credit-card fraud detection (2018, methodology): “[Dal Pozzolo and Bontempi, 2015] applied this technique successfully to credit-card fraud detection.”