2 papers
cs.LG2020
TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling
Pedro Mendes, Maria Casimiro, Paolo Romano +1
This work introduces TrimTuner, the first system for optimizing machine learning jobs in the cloud to exploit sub-sampling techniques to reduce the cost of the optimization process…
cs.DC2019
Lynceus: Cost-efficient Tuning and Provisioning of Data Analytic Jobs
Maria Casimiro, Diego Didona, Paolo Romano +3
Modern data analytic and machine learning jobs find in the cloud a natural deployment platform to satisfy their notoriously large resource requirements. Yet, to achieve cost effici…