1 citations · 1 across the 1 of their papers we have counts for
6 papers
Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networks
Yuxin Dong, Jianhua Yao, Jiajing Wang +3
Financial fraud refers to the act of obtaining financial benefits through dishonest means. Such behavior not only disrupts the order of the financial market but also harms economic…
Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function
Hongye Zheng, Bingxing Wang, Minheng Xiao +3
Adaptive optimizers are pivotal in guiding the weight updates of deep neural networks, yet they often face challenges such as poor generalization and oscillation issues. To counter…
Electroencephalogram Emotion Recognition via AUC Maximization
Minheng Xiao
Imbalanced datasets pose significant challenges in areas including neuroscience, cognitive science, and medical diagnostics, where accurately detecting minority classes is essentia…
Root Cause Attribution of Delivery Risks via Causal Discovery with Reinforcement Learning
Minheng Xiao
This paper presents a novel approach to root cause attribution of delivery risks within supply chains by integrating causal discovery with reinforcement learning. As supply chains…
Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning
Zixiang Wang, Hao Yan, Changsong Wei +2
The behavior decision-making subsystem is a key component of the autonomous driving system, which reflects the decision-making ability of the vehicle and the driver, and is an impo…
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems
Minheng Xiao, Zhizhong Wu
This paper introduces the Multiple Greedy Quasi-Newton (MGSR1-SP) method, a novel approach to solving strongly-convex-strongly-concave (SCSC) saddle point problems. Our method enha…