2 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…