activity
20132021
most citedUsing link and content over time for embedding generation in Dynamic Attributed Networks

16 citations · 29 across the 8 of their papers we have counts for

collaborators

8 papers

cs.DC2021

Context-aware Execution Migration Tool for Data Science Jupyter Notebooks on Hybrid Clouds

Renato L. F. Cunha, Lucas V. Real, Renan Souza +2

Interactive computing notebooks, such as Jupyter notebooks, have become a popular tool for developing and improving data-driven models. Such notebooks tend to be executed either in…

cs.LG2018★ 16 cited

Using link and content over time for embedding generation in Dynamic Attributed Networks

Ana Paula Appel, Renato L. F. Cunha, Charu C. Aggarwal +1

In this work, we consider the problem of combining link, content and temporal analysis for community detection and prediction in evolving networks. Such temporal and content-rich n…

cs.DC2018★ 9 cited

JobPruner: A Machine Learning Assistant for Exploring Parameter Spaces in HPC Applications

Bruno Silva, Marco A. S. Netto, Renato L. F. Cunha

High Performance Computing (HPC) applications are essential for scientists and engineers to create and understand models and their properties. These professionals depend on the exe…

cs.LG2017★ 3 cited

Determining Song Similarity via Machine Learning Techniques and Tagging Information

Renato L. F. Cunha, Evandro Caldeira, Luciana Fujii

The task of determining item similarity is a crucial one in a recommender system. This constitutes the base upon which the recommender system will work to determine which items are…

cs.DC2016★ 1 cited

SLA-aware Interactive Workflow Assistant for HPC Parameter Sweeping Experiments

Bruno Silva, Marco A. S. Netto, Renato L. F. Cunha

A common workflow in science and engineering is to (i) setup and deploy large experiments with tasks comprising an application and multiple parameter values; (ii) generate intermed…

cs.DC2016

Helping HPC Users Specify Job Memory Requirements via Machine Learning

Eduardo R. Rodrigues, Renato L. F. Cunha, Marco A. S. Netto +1

Resource allocation in High Performance Computing (HPC) settings is still not easy for end-users due to the wide variety of application and environment configuration options. Users…

cs.DC2016

Job Placement Advisor Based on Turnaround Predictions for HPC Hybrid Clouds

Renato L. F. Cunha, Eduardo R. Rodrigues, Leonardo P. Tizzei +1

Several companies and research institutes are moving their CPU-intensive applications to hybrid High Performance Computing (HPC) cloud environments. Such a shift depends on the cre…

cs.DC2013

Patience-aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom

Carlos Cardonha, Marcos D. Assunção, Marco A. S. Netto +2

Scheduling of service requests in Cloud computing has traditionally focused on the reduction of pre-service wait, generally termed as waiting time. Under certain conditions such as…