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cs.DB2026
MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning
Beicheng Xu, Lingching Tung, Yuchen Wang +2
Apache Spark SQL is a cornerstone of modern big data analytics.However,optimizing Spark SQL performance is challenging due to its vast configuration space and the prohibitive cost…
cs.LG2026
CoFEH: LLM-driven Feature Engineering Empowered by Collaborative Bayesian Hyperparameter Optimization
Beicheng Xu, Keyao Ding, Wei Liu +2
Feature Engineering (FE) is pivotal in automated machine learning (AutoML) but remains a bottleneck for traditional methods, which operate within rigid search spaces and lack domai…
cs.LG2026
Tree-Structured Synergy of Large Language Models and Bayesian Optimization for Efficient CASH
Beicheng Xu, Weitong Qian, Lingching Tung +2
To lower the expertise barrier in machine learning, the AutoML community has focused on the CASH problem, which jointly automates algorithm selection and hyperparameter tuning. Whi…