5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.DB2026
Can Large Language Models be a Cardinality Estimator? An Empirical study
Liangzu Liu, Yiyan Wang, Yinjun Wu +8
Cardinality estimation (CardEst) still remains a challenging problem for DBMS. Recent years have witnessed the success of ML-based cardinality estimators in outperforming tradition…
cs.DB2023★ 1 cited
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
Xinyi Zhang, Zhuo Chang, Hong Wu +5
Recently using machine learning (ML) based techniques to optimize modern database management systems has attracted intensive interest from both industry and academia. With an objec…
cs.DB2021★ 5 cited
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation
Xinyi Zhang, Zhuo Chang, Yang Li +4
Recently, using automatic configuration tuning to improve the performance of modern database management systems (DBMSs) has attracted increasing interest from the database communit…