Towards a General Framework for ML-based Self-tuning Databases

no code implementations • 16 Nov 2020 • Thomas Schmied, Diego Didona, Andreas Döring, Thomas Parnell, Nikolas Ioannou

Machine learning (ML) methods have recently emerged as an effective way to perform automated parameter tuning of databases.

Bayesian Optimization Reinforcement Learning (RL) +1

On Bootstrapping Machine Learning Performance Predictors via Analytical Models

no code implementations • 19 Oct 2014 • Diego Didona, Paolo Romano

Performance modeling typically relies on two antithetic methodologies: white box models, which exploit knowledge on system's internals and capture its dynamics using analytical approaches, and black box techniques, which infer relations among the input and output variables of a system based on the evidences gathered during an initial training phase.

BIG-bench Machine Learning