Template-based semi-automatic workflow construction for gene expression data analysis. - Jiri Belohradsky; David A. Monge; Filip Zelezný; Matej Holec; Carlos García Garino (CBMS, 2011)

Adaptive Spot-Instances Aware Autoscaling for Scientific Workflows on the Cloud. - David A. Monge; Carlos García Garino (CARLA, 2014)

Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. - David A. Monge; Matej Holec; Filip Zelezný; Carlos García Garino (CARLA, 2014)

LOGOS: Enabling Local Resource Managers for the Efficient Support of Data-Intensive Workflows within Grid Sites. - David A. Monge; Carlos García Garino (Comput. Informatics, 2014)

Ensemble learning of runtime prediction models for gene-expression analysis workflows. - David A. Monge; Matej Holec; Filip Zelezný; Carlos García Garino (Clust. Comput., 2015)

Markov Decision Process to Dynamically Adapt Spots Instances Ratio on the Autoscaling of Scientific Workflows in the Cloud. - Yisel Gari; David A. Monge; Cristian Mateos; Carlos García Garino (CARLA, 2017)

FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC. - Josef Spillner; Cristian Mateos; David A. Monge (CARLA, 2017)

A performance comparison of data-aware heuristics for scheduling jobs in mobile grids. - Matías Hirsch; Cristian Mateos; Juan Manuel Rodriguez; Alejandro Zunino; Yisel Gari; David A. Monge (CLEI, 2017)

Autoscaling scientific workflows on the cloud by combining on-demand and spot instances. - David A. Monge; Yisel Gari; Cristian Mateos; Carlos García Garino (Comput. Syst. Sci. Eng., 2017)

Meta-heuristic based autoscaling of cloud-based parameter sweep experiments with unreliable virtual machines instances. - David A. Monge; Elina Pacini; Cristian Mateos; Carlos García Garino (Comput. Electr. Eng., 2018)

An NSGA-III-Based Multi-objective Intelligent Autoscaler for Executing Engineering Applications in Cloud Infrastructures. - Virginia Yannibelli; Elina Pacini; David A. Monge; Cristian Mateos; Guillermo Rodríguez 002 (MICAI (1), 2020)

Learning budget assignment policies for autoscaling scientific workflows in the cloud. - Yisel Gari; David A. Monge; Cristian Mateos; Carlos García Garino (Clust. Comput., 2020)

Reinforcement Learning-based Autoscaling of Workflows in the Cloud: A Survey. - Yisel Gari; David A. Monge; Elina Pacini; Cristian Mateos; Carlos García Garino (CoRR, 2020)

CMI: An online multi-objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines. - David A. Monge; Elina Pacini; Cristian Mateos; Enrique Alba 001; Carlos García Garino (J. Netw. Comput. Appl., 2020)

A Comparative Analysis of NSGA-II and NSGA-III for Autoscaling Parameter Sweep Experiments in the Cloud. - Virginia Yannibelli; Elina Pacini; David A. Monge; Cristian Mateos; Guillermo Rodríguez 002 (Sci. Program., 2020)

Endowing the MIA Cloud Autoscaler with Adaptive Evolutionary and Particle Swarm Multi-Objective Optimization Algorithms. - Virginia Yannibelli; Elina Pacini; David A. Monge; Cristian Mateos; Guillermo Rodríguez 002 (MICAI (1), 2021)

Reinforcement learning-based application Autoscaling in the Cloud: A survey. - Yisel Gari; David A. Monge; Elina Pacini; Cristian Mateos; Carlos García Garino (Eng. Appl. Artif. Intell., 2021)

A Q-learning approach for the autoscaling of scientific workflows in the Cloud. - Yisel Gari; David A. Monge; Cristian Mateos (Future Gener. Comput. Syst., 2022)

Online RL-based cloud autoscaling for scientific workflows: Evaluation of Q-Learning and SARSA. - Yisel Gari; Elina Pacini; Luciano Robino; Cristian Mateos; David A. Monge (Future Gener. Comput. Syst., 2024)