CoLSE: A Lightweight and Robust Hybrid Model for Cardinality Estimation
Research#Cardinality🔬 Research|Analyzed: Jan 10, 2026 11:25•
Published: Dec 14, 2025 10:08
•1 min read
•ArXivAnalysis
This paper presents CoLSE, a novel approach to single-table cardinality estimation, crucial for query optimization in database systems. The hybrid model, incorporating learned components and Cumulative Distribution Functions (CDFs), promises improved accuracy and robustness compared to existing methods.
Key Takeaways
- •CoLSE proposes a lightweight and robust hybrid learned model.
- •The model leverages Joint CDFs for cardinality estimation.
- •The research is published on ArXiv, indicating early-stage research.
Reference / Citation
View Original"CoLSE utilizes a hybrid approach, combining learned models with Joint Cumulative Distribution Functions (JCDFs)."