activity
20182022
most citedRisk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty

1 citations · 2 across the 5 of their papers we have counts for

collaborators
Showing cs.DBShow all

1 paper · 1 filter

cs.DB2021

UDO: Universal Database Optimization using Reinforcement Learning

Junxiong Wang, Immanuel Trummer, Debabrota Basu

UDO is a versatile tool for offline tuning of database systems for specific workloads. UDO can consider a variety of tuning choices, reaching from picking transaction code variants…