Evgeny Burnaev

Sequence embeddings help to identify fraudulent cases in healthcare insurance

2019 · arXiv (Cornell University)

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. It has been estimated that roughly $10$ percent of the …

NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing

2022 · IEEE Access

Neural Architecture Search (NAS) is a promising and rapidly evolving research area. Training a large number of neural networks requires an exceptional amount of computational power, which makes NAS unreachable for those researchers who have …

Adversarial Attacks on Deep Models for Financial Transaction Records

2021 · arXiv (Cornell University)

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 the NLP community, posing a challenge due to their tremendous number …

A Differentiable Language Model Adversarial Attack on Text Classifiers

2022 · IEEE Access

Transformer models play a crucial role in state of the art solutions to problems arising in the field of natural language processing (NLP). They have billions of parameters and are typically considered as black boxes. …

Kernel Neural Optimal Transport

2022 · arXiv (Cornell University)

We study the Neural Optimal Transport (NOT) algorithm which uses the general optimal transport formulation and learns stochastic transport plans. We show that NOT with the weak quadratic cost might learn fake plans which are …