53 citations · 111 across the 12 of their papers we have counts for
13 papers
Lero: A Learning-to-Rank Query Optimizer
Rong Zhu, Wei Chen, Bolin Ding +4
A recent line of works apply machine learning techniques to assist or rebuild cost-based query optimizers in DBMS. While exhibiting superiority in some benchmarks, their deficienci…
Estimation of Doubly-Dispersive Channels in Linearly Precoded Multicarrier Systems Using Smoothness Regularization
Andreas Pfadler, Tom Szollmann, Peter Jung +1
In this paper, we propose a novel channel estimation scheme for pulse-shaped multicarrier systems using smoothness regularization for ultra-reliable low-latency communication (URLL…
Baihe: SysML Framework for AI-driven Databases
Andreas Pfadler, Rong Zhu, Wei Chen +4
We present Baihe, a SysML Framework for AI-driven Databases. Using Baihe, an existing relational database system may be retrofitted to use learned components for query optimization…
Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size
Rong Zhu, Tianjing Zeng, Andreas Pfadler +3
Cardinality estimation (CardEst), a central component of the query optimizer, plays a significant role in generating high-quality query plans in DBMS. The CardEst problem has been…
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation
Yuxing Han, Ziniu Wu, Peizhi Wu +11
Cardinality estimation (CardEst) plays a significant role in generating high-quality query plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced…
QoS Prediction for 5G Connected and Automated Driving
Apostolos Kousaridas, Ramya Panthangi Manjunath, Jose Mauricio Perdomo +4
5G communication system can support the demanding quality-of-service (QoS) requirements of many advanced vehicle-to-everything (V2X) use cases. However, the safe and efficient driv…