5 papers
Benefits of Shifting Passenger Traffic from Air to Rail: A Case Study of California High-Speed Rail
Kaijing Ding, Lu Dai, Mark Hansen
This study provides a method to quantify the benefits of shifting passenger traffic from air to high-speed rail from the perspective of flight-delay cost reduction. We first estima…
Machine Learning Approaches to Clinical Risk Prediction: Multi-Scale Temporal Alignment in Electronic Health Records
Wei-Chen Chang, Lu Dai, Ting Xu
This study proposes a risk prediction method based on a Multi-Scale Temporal Alignment Network (MSTAN) to address the challenges of temporal irregularity, sampling interval differe…
Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networks
Lu Dai, Wenxuan Zhu, Xuehui Quan +3
To improve the identification of potential anomaly patterns in complex user behavior, this paper proposes an anomaly detection method based on a deep mixture density network. The m…
Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining
Yingbin Liang, Lu Dai, Shuo Shi +3
Complex data mining has wide application value in many fields, especially in the feature extraction and classification tasks of unlabeled data. This paper proposes an algorithm bas…
Federated Learning for Cross-Domain Data Privacy: A Distributed Approach to Secure Collaboration
Yiwei Zhang, Jie Liu, Jiawei Wang +3
This paper proposes a data privacy protection framework based on federated learning, which aims to realize effective cross-domain data collaboration under the premise of ensuring d…