Avatar

Giorgio Vinciguerra

PhD student

Università di Pisa

Biography

I’m a PhD student in Computer Science at the University of Pisa, currently member of the A³ Lab led by Prof. Paolo Ferragina.

I’m working on multicriteria learned data structures, that is, data structures that adapt themselves to the context of use by optimising one or more computational resources within some user-defined constraints.

Interests

  • Compact data structures
  • Data compression
  • Learned indexes

Education

  • M.Sc. in Computer Science, 2018

    University of Pisa

  • B.Sc. in Computer Science, 2016

    University of Pisa

Papers

A “learned” approach to quicken and compress rank/select dictionaries

We address the well-known problem of designing, implementing and experimenting compressed data structures for supporting rank and …
Antonio Boffa, Paolo Ferragina, Giorgio Vinciguerra

Why are learned indexes so effective?

A recent trend in algorithm design consists of augmenting classic data structures with machine learning models, which are better suited …
Paolo Ferragina, Fabrizio Lillo, Giorgio Vinciguerra
PDF Code Slides Video

The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds

We present the first learned index that supports predecessor, range queries and updates within provably efficient time and space bounds …
Paolo Ferragina, Giorgio Vinciguerra
PDF Code Project Slides Video DOI

Learned data structures

Very recently, the unexpected combination of data structures and machine learning has led to the development of a new area of research, …
Paolo Ferragina, Giorgio Vinciguerra
PDF DOI

Superseding traditional indexes by orchestrating learning and geometry

We design the first learned index that solves the dictionary problem with time and space complexity provably better than classic data …
Giorgio Vinciguerra, Paolo Ferragina, Michele Miccinesi
PDF arXiv

Projects

PyGM

Python library of sorted containers with state-of-the-art query performance and compressed memory usage.

PGM-index

A data structure enabling fast searches in arrays of billions of items using orders of magnitude less space than traditional indexes.

CSS-tree

A C++11 implementation of the Cache Sensitive Search tree.

NN Weaver

A Python library to build and train feedforward neural networks, with hyperparameters tuning capabilities.

Talks

Learned indexes
Jan 21, 2020 16:00 DASlab @ Harvard SEAS
The PGM-index: a multicriteria, compressed and learned approach to data indexing
Sep 6, 2019 11:00 Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Superseding traditional indexes with multicriteria data structures
May 14, 2019 13:00 Dipartimento di Informatica
Multicriteria data structures
Mar 18, 2019 11:00 Dipartimento di Informatica

Teaching

Teaching assistant for:

Knowledge is like a sphere; the greater its volume, the larger its contact with the unknown.

― Blaise Pascal

Contact

  • +39 050 2213133
  • Room 282
    Dipartimento di Informatica
    Largo Bruno Pontecorvo 3, Pisa, 56127