3 papers
cs.LG2025
Deep Q-Learning-Based Intelligent Scheduling for ETL Optimization in Heterogeneous Data Environments
Kangning Gao, Yi Hu, Cong Nie +1
This paper addresses the challenges of low scheduling efficiency, unbalanced resource allocation, and poor adaptability in ETL (Extract-Transform-Load) processes under heterogeneou…
cs.LG2025
Deep Learning Approach to Anomaly Detection in Enterprise ETL Processes with Autoencoders
Xin Chen, Saili Uday Gadgil, Kangning Gao +2
An anomaly detection method based on deep autoencoders is proposed to address anomalies that often occur in enterprise-level ETL data streams. The study first analyzes multiple typ…
cs.CV2024
Future Does Matter: Boosting 3D Object Detection with Temporal Motion Estimation in Point Cloud Sequences
Rui Yu, Runkai Zhao, Cong Nie +3
Accurate and robust LiDAR 3D object detection is essential for comprehensive scene understanding in autonomous driving. Despite its importance, LiDAR detection performance is limit…