8 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
Adversarial Attacks on Deep Models for Financial Transaction Records
Ivan Fursov, Matvey Morozov, Nina Kaploukhaya +7
Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in…
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers
I. Fursov, A. Zaytsev, N. Kluchnikov +2
An adversarial attack paradigm explores various scenarios for the vulnerability of deep learning models: minor changes of the input can force a model failure. Most of the state of…
Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world
Ivan Fursov, Alexey Zaytsev, Nikita Kluchnikov +2
Deep learning models suffer from a phenomenon called adversarial attacks: we can apply minor changes to the model input to fool a classifier for a particular example. The literatur…
Sequence embeddings help to identify fraudulent cases in healthcare insurance
I. Fursov, A. Zaytsev, R. Khasyanov +2
Fraud causes substantial costs and losses for companies and clients in the finance and insurance industries. Examples are fraudulent credit card transactions or fraudulent claims.…