29 citations · 29 across the 4 of their papers we have counts for
4 papers
BQSched: A Non-intrusive Scheduler for Batch Concurrent Queries via Reinforcement Learning
Chenhao Xu, Chunyu Chen, Jinglin Peng +2
Most large enterprises build predefined data pipelines and execute them periodically to process operational data using SQL queries for various tasks. A key issue in minimizing the…
Auto-FP: An Experimental Study of Automated Feature Preprocessing for Tabular Data
Danrui Qi, Jinglin Peng, Yongjun He +1
Classical machine learning models, such as linear models and tree-based models, are widely used in industry. These models are sensitive to data distribution, thus feature preproces…
DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python
Jinglin Peng, Weiyuan Wu, Brandon Lockhart +6
Exploratory Data Analysis (EDA) is a crucial step in any data science project. However, existing Python libraries fall short in supporting data scientists to complete common EDA ta…
Explaining Inference Queries with Bayesian Optimization
Brandon Lockhart, Jinglin Peng, Weiyuan Wu +2
Obtaining an explanation for an SQL query result can enrich the analysis experience, reveal data errors, and provide deeper insight into the data. Inference query explanation seeks…