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Online Non-linear Gradient Boosting in Multi-latent Spaces.

, , , , и . IDA, том 11191 из Lecture Notes in Computer Science, стр. 99-110. Springer, (2018)

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Liyun Zhu

Liyun Zhao

Hongxia He

Ning He

Chunmao He

 

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Multiple perspectives HMM-based feature engineering for credit card fraud detection., , , , , , и . SAC, стр. 1359-1361. ACM, (2019)Master Your Metrics with Calibration., , , , и . IDA, том 12080 из Lecture Notes in Computer Science, стр. 457-469. Springer, (2020)Dataset Shift Quantification for Credit Card Fraud Detection., , , , , , и . AIKE, стр. 97-100. IEEE, (2019)Dual Sequential Variational Autoencoders for Fraud Detection., , , , и . IDA, том 12080 из Lecture Notes in Computer Science, стр. 14-26. Springer, (2020)Online Non-linear Gradient Boosting in Multi-latent Spaces., , , , и . IDA, том 11191 из Lecture Notes in Computer Science, стр. 99-110. Springer, (2018)Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection., , , , , и . ICTAI, стр. 1351-1355. IEEE, (2019)NAG: Neural feature aggregation framework for credit card fraud detection., , , , и . ICDM, стр. 92-101. IEEE, (2020)Embeddings of Categorical Variables for Sequential Data in Fraud Context., , и . AMLTA, том 723 из Advances in Intelligent Systems and Computing, стр. 542-552. Springer, (2018)Deep-Learning Domain Adaptation Techniques for Credit Cards Fraud Detection., , , , и . INNSBDDL, стр. 78-88. Springer, (2019)Non-Linear Gradient Boosting for Class-Imbalance Learning., , , и . LIDTA@ECML/PKDD, том 94 из Proceedings of Machine Learning Research, стр. 38-51. PMLR, (2018)