3 papers
cs.LG2025
Estimating Deep Learning energy consumption based on model architecture and training environment
Santiago del Rey, LuÃs Cruz, Xavier Franch +1
To raise awareness of the environmental impact of deep learning (DL), many studies estimate the energy use of DL systems. However, energy estimates during DL training often rely on…
cs.SE2025
Aggregating empirical evidence from data strategy studies: a case on model quantization
Santiago del Rey, Paulo Sérgio Medeiros dos Santos, Guilherme Horta Travassos +2
Background: As empirical software engineering evolves, more studies adopt data strategiesapproaches that investigate digital artifacts such as models, source code, or system log…
cs.SE2025
Addressing Quality Challenges in Deep Learning: The Role of MLOps and Domain Knowledge
Santiago del Rey, Adrià Medina, Xavier Franch +1
Deep learning (DL) systems present unique challenges in software engineering, especially concerning quality attributes like correctness and resource efficiency. While DL models exc…