12 citations · 27 across the 15 of their papers we have counts for
16 papers
Pareto Optimal Compression of Genomic Dictionaries, with or without Random Access in Main Memory
Raffaele Giancarlo, Gennaro Grimaudo
Motivation: A Genomic Dictionary, i.e., the set of the k-mers appearing in a genome, is a fundamental source of genomic information: its collection is the first step in strategic c…
A Critical Analysis of Classifier Selection in Learned Bloom Filters
Dario Malchiodi, Davide Raimondi, Giacomo Fumagalli +2
Learned Bloom Filters, i.e., models induced from data via machine learning techniques and solving the approximate set membership problem, have recently been introduced with the aim…
A New Class of String Transformations for Compressed Text Indexing
Raffaele Giancarlo, Giovanni Manzini, Antonio Restivo +2
Introduced about thirty years ago in the field of Data Compression, the Burrows-Wheeler Transform (BWT) is a string transformation that, besides being a booster of the performance…
Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platform
Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo
Learned Indexes are a novel approach to search in a sorted table. A model is used to predict an interval in which to search into and a Binary Search routine is used to finalize the…
On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters
Giacomo Fumagalli, Davide Raimondi, Raffaele Giancarlo +2
Bloom Filters are a fundamental and pervasive data structure. Within the growing area of Learned Data Structures, several Learned versions of Bloom Filters have been considered, yi…
Burrows Wheeler Transform on a Large Scale: Algorithms Implemented in Apache Spark
Ylenia Galluzzo, Raffaele Giancarlo, Mario Randazzo +1
With the rapid growth of Next Generation Sequencing (NGS) technologies, large amounts of "omics" data are daily collected and need to be processed. Indexing and compressing large s…