11 citations · 17 across the 4 of their papers we have counts for
6 papers
Learned Static Function Data Structures
Stefan Hermann, Hans-Peter Lehmann, Giorgio Vinciguerra +1
We consider the task of constructing a data structure for associating a static set of keys with values, while allowing arbitrary output values for queries involving keys outside th…
Learned Compression of Nonlinear Time Series With Random Access
Andrea Guerra, Giorgio Vinciguerra, Antonio Boffa +1
Time series play a crucial role in many fields, including finance, healthcare, industry, and environmental monitoring. The storage and retrieval of time series can be challenging d…
Grafite: Taming Adversarial Queries with Optimal Range Filters
Marco Costa, Paolo Ferragina, Giorgio Vinciguerra
Range filters allow checking whether a query range intersects a given set of keys with a chance of returning a false positive answer, thus generalising the functionality of Bloom f…
Learned Monotone Minimal Perfect Hashing
Paolo Ferragina, Hans-Peter Lehmann, Peter Sanders +1
A Monotone Minimal Perfect Hash Function (MMPHF) constructed on a set S of keys is a function that maps each key in S to its rank. On keys not in S, the function returns an arbitra…
The PGM-index: a multicriteria, compressed and learned approach to data indexing
Paolo Ferragina, Giorgio Vinciguerra
The recent introduction of learned indexes has shaken the foundations of the decades-old field of indexing data structures. Combining, or even replacing, classic design elements su…
Superseding traditional indexes by orchestrating learning and geometry
Giorgio Vinciguerra, Paolo Ferragina, Michele Miccinesi
We design the first learned index that solves the dictionary problem with time and space complexity provably better than classic data structures for hierarchical memories, such as…