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Found 6 papers, 2 papers with code
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Anomaly detection aims to distinguish abnormal instances that deviate significantly from the majority of benign ones.
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
Thus, in this paper, we further propose a transfer framework to tackle the cross-domain fraud detection problem, which aims to transfer knowledge from existing domains (source domains) with enough and mature data to improve the performance in the new domain (target domain).
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance.
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection
In this paper, we propose the Dual Importance-aware Factorization Machines (DIFM), which exploits the internal field information among users' behavior sequence from dual perspectives, i. e., field value variations and field interactions simultaneously for fraud detection.
Adapted tree boosting for Transfer Learning
Secure online transaction is an essential task for e-commerce platforms.
Scalable String Reconciliation by Recursive Content-Dependent Shingling
We consider the problem of reconciling similar, but remote, strings with minimum communication complexity.
Information Theory Information Theory
