DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs-Reference-Cited by-同舟云学术

DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
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Author:

Assumpcao Henrique S.¹,Souza Fabricio¹,Campos Leandro Lacerda²,de Castro Pires Vinicius T.²,de Almeida Paulo M. Laurentys³,Murai Fabricio⁴

Affiliation:

1. Universidade Federal de Minas Gerais

2. Universidade Federal de Minas Gerais,InterMind (Inter&Co)

3. InterMind (Inter&Co)

4. Universidade Federal de Minas Gerais,Worcester Polytechnic Institute

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10021010.pdf?arnumber=10021010

Reference15 articles.

1. Lightgbm: A highly efficient gradient boosting decision tree;ke;Advances in neural information processing systems,2017

2. Delator: Money laundering detection via multi-task learning on large transaction graphs;assumpção,2022

3. Fighting biases with dynamic boosting;dorogush;CoRR,2017

4. Dgl-ke: Training knowledge graph embeddings at scale;zheng;Proceedings of ACM SIGIR International Conference on Research and Development in Information Retrieval,2020

5. Graph-Based LSTM for Anti-money Laundering: Experimenting Temporal Graph Convolutional Network with Bitcoin Data

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3. DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs;2022 IEEE International Conference on Big Data (Big Data);2022-12-17