1 citations · 1 across the 8 of their papers we have counts for
8 papers
From Code Archival to Knowledge Graph: Bridging Software Heritage, COAR Notify and Wikidata
Camillo Carlo Pellizzari di San Girolamo, Francesco Tosoni
Software is a first-class scientific object, yet validated links between source code and the scholarly record remain largely absent from the Linked Open Data (LOD) cloud, isolating…
An Analysis and Implementation of Seam Carving for Content-Aware Image Resizing
Francesco Tosoni
Seam carving is a classical content-aware image resizing operator that modifies the width or height of an image by repeatedly removing (or inserting) seams, i.e., 8-connected monot…
Extended Depth-First Representations of -trees
Gabriel Carmona, Paolo Ferragina, Giovanni Manzini +1
In this paper, we study static, computation-friendly, lossless compression formats for graphs, focusing on memory locality and operational efficiency of -trees. We observe tha…
MediaWiki Code2Code Search: Neural Retrieval for the Semantic Discovery of Open-Source Software Entities
Francesco Tosoni
Code search in large-scale ecosystems is often hindered by the lexical gap between user queries and implementation details, alongside the trade-off between the low latency of tradi…
Right Multiplication on Grammar-Compressed Matrices: A Streaming, Memory-Bounded GPU Engine
Francesco Tosoni, Gabriele Mencagli
Grammar-compressed matrices (the mm-repair family) store a matrix's non-zero structure as a RePair straight-line program (SLP), supporting matrix-vector products in time and space…
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…
Toward Greener Matrix Operations by Lossless Compressed Formats
Francesco Tosoni, Philip Bille, Valerio Brunacci +3
Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time…
Improving Matrix-vector Multiplication via Lossless Grammar-Compressed Matrices
Paolo Ferragina, Travis Gagie, Dominik Köppl +4
As nowadays Machine Learning (ML) techniques are generating huge data collections, the problem of how to efficiently engineer their storage and operations is becoming of paramount…