Generative Pretraining at Scale: Transformer-Based Encoding of Transactional Behavior for Fraud Detection

no code implementations • 22 Dec 2023 • Ze Yu Zhao, Zheng Zhu, Guilin Li, Wenhan Wang, Bo wang

In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems.

Anomaly Detection Fraud Detection

On Designing Multi-UAV aided Wireless Powered Dynamic Communication via Hierarchical Deep Reinforcement Learning

no code implementations • 13 Dec 2023 • Ze Yu Zhao, Yue Ling Che, Sheng Luo, Gege Luo, Kaishun Wu, Victor C. M. Leung

We then propose a new multi-agent based hierarchical deep reinforcement learning (MAHDRL) framework with two tiers to solve the problem efficiently, where the soft actor critic (SAC) policy is designed in tier-1 to determine each UAV's continuous trajectory and binary WET decision over time slots, and the deep-Q learning (DQN) policy is designed in tier-2 to determine each UAV's binary WDC decisions over sub-slots under the given UAV trajectory from tier-1.

Deep Reinforcement Learning Q-Learning