Very recently, the unexpected combination of data structures and machine learning has led to the development of a new area of research, called learned data structures. Their distinguishing trait is the ability to reveal and exploit patterns and trends in the input data for achieving more efficiency in time and space, compared to previously known data structures. The goal of this chapter is to provide the first comprehensive survey of these results and to stimulate further research in this promising area.

Learned Data Structures

Paolo Ferragina;
2020-01-01

Abstract

Very recently, the unexpected combination of data structures and machine learning has led to the development of a new area of research, called learned data structures. Their distinguishing trait is the ability to reveal and exploit patterns and trends in the input data for achieving more efficiency in time and space, compared to previously known data structures. The goal of this chapter is to provide the first comprehensive survey of these results and to stimulate further research in this promising area.
2020
978-3-030-43882-1
File in questo prodotto:
File Dimensione Formato  
BookChapter__Learned_data_structures.pdf

accesso aperto

Tipologia: Documento in Pre-print/Submitted manuscript
Licenza: Copyright dell'editore
Dimensione 382.01 kB
Formato Adobe PDF
382.01 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/566814
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 26
social impact