| HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges MAS Netto, RN Calheiros, ER Rodrigues, RLF Cunha, R Buyya ACM Computing Surveys (CSUR) 51 (1), 2018 | 238 | 2018 |
| DeepDownscale: A deep learning strategy for high-resolution weather forecast ER Rodrigues, I Oliveira, R Cunha, M Netto 2018 IEEE 14th International Conference on e-Science (e-Science), 415-422, 2018 | 133 | 2018 |
| A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast RLF Cunha, B Silva, MAS Netto 2018 IEEE 14th International Conference on e-Science (e-Science), 423-430, 2018 | 109 | 2018 |
| Evaluating auto-scaling strategies for cloud computing environments MAS Netto, C Cardonha, RLF Cunha, MD Assunçao 2014 IEEE 22nd International Symposium on Modelling, Analysis & Simulation …, 2014 | 104 | 2014 |
| Job placement advisor based on turnaround predictions for HPC hybrid clouds RLF Cunha, ER Rodrigues, LP Tizzei, MAS Netto Future Generation Computer Systems 67, 35-46, 2017 | 51 | 2017 |
| RAG vs fine-tuning: Pipelines, tradeoffs, and a case study on agriculture A Balaguer, V Benara, RLF Cunha, T Hendry, D Holstein, J Marsman, ... arXiv preprint arXiv:2401.08406, 2024 | 45 | 2024 |
| Helping HPC users specify job memory requirements via machine learning ER Rodrigues, RLF Cunha, MAS Netto, M Spriggs 2016 Third International Workshop on HPC User Support Tools (HUST), 6-13, 2016 | 45 | 2016 |
| Impact of user patience on auto-scaling resource capacity for cloud services MD De Assuncao, CH Cardonha, MAS Netto, RLF Cunha Future Generation Computer Systems 55, 41-50, 2016 | 45 | 2016 |
| Temporally evolving community detection and prediction in content-centric networks AP Appel, RLF Cunha, CC Aggarwal, MM Terakado ECML PKDD 2018, 1-16, 2018 | 32 | 2018 |
| User interface and system supporting user decision making and readjustments in computer-executable job allocations in the cloud MAS Netto, NB Sultanum, RLF Cunha US Patent 10,067,798, 2018 | 28 | 2018 |
| Hybrid cloud operation planning and optimization APD Binotto, RLDF Cunha, ER Rodrigues US Patent 10,929,792, 2021 | 22 | 2021 |
| Estimating crop yields with remote sensing and deep learning RL de Freitas Cunha, B Silva 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS …, 2020 | 22 | 2020 |
| Auto-scaling thresholds in elastic computing environments CH Cardonha, MD de Assuncao, RL de Freitas Cunha, MAS Netto US Patent 9,513,935, 2016 | 19 | 2016 |
| An Artificial Intelligence system to help the player of Real-Time Strategy games RL de Freitas Cunha, L Chaimowicz 2010 Brazilian Symposium on Games and Digital Entertainment, 71-81, 2010 | 17 | 2010 |
| JobPruner: A machine learning assistant for exploring parameter spaces in HPC applications B Silva, MAS Netto, RLF Cunha Future Generation Computer Systems 83, 144-157, 2018 | 16 | 2018 |
| Deciding when and how to move HPC jobs to the cloud MAS Netto, RLF Cunha, N Sultanum Computer 48 (11), 86-89, 2015 | 14 | 2015 |
| Exploiting user patience for scaling resource capacity in cloud services RLF Cunha, MD Assunçao, C Cardonha, MAS Netto 2014 IEEE 7th International Conference on Cloud Computing, 448-455, 2014 | 13 | 2014 |
| RAG vs fine-tuning: pipelines, tradeoffs, and a case study on agriculture A Gupta, A Shirgaonkar, ADL Balaguer, B Silva, D Holstein, D Li, ... arXiv preprint arXiv:2401.08406, 2024 | 12 | 2024 |
| Context-aware execution migration tool for data science jupyter notebooks on hybrid clouds RLF Cunha, LCV Real, R Souza, B Silva, MAS Netto 2021 IEEE 17th international conference on eScience (eScience), 30-39, 2021 | 11 | 2021 |
| Towards a common environment for learning scheduling algorithms RL de Freitas Cunha, L Chaimowicz 2020 28th International Symposium on Modeling, Analysis, and Simulation of …, 2020 | 11 | 2020 |
Marco A. S. NettoMicrosoft, Azure HPC+AIยืนยันอีเมลแล้วที่ ieee.org