2 papers
cs.DS2026
The Energy-Throughput Trade-off in Lossless-Compressed Source Code Storage
Paolo Ferragina, Francesco Tosoni
Retrieving data from large-scale source code archives is vital for AI training, neural-based software analysis, and information retrieval, to cite a few. This paper studies and exp…
cs.DS2024
Balanced Learned Sort: a new learned model for fast and balanced item bucketing
Paolo Ferragina, Mattia Odorisio
This paper aims to better understand the strengths and limitations of adopting learned-based approaches in sequential sorting numerical data, via two main research steps. First, we…