Special Issue: Algorithms and Data-Structures for Compressed Computation
Submission Deadline: 30 January 2021
Dear Colleagues,
As the production of massive data has outpaced Moore's law in many
scientific areas, the very notion of algorithm is shaping up to keep the
pace. Today's algorithms must not only be able to deal with large amounts
of data, they also must be capable to use resources close to their
theoretical limits. Against this landscape, compression has become a
fundamental tool to make the storage of this kind of data possible in the
first place.
While motivated by the fact that massive data are often very compressible,
this approach poses interesting algorithmic challenges: Can we compute
directly on compressed data without first decompressing it? Can we propose
measures and frameworks to compare different approaches? Can different
techniques for compressed computation be unified?
Thanks to more than two decades of successful research on the subject,
today we know that many algorithmic marvels are indeed possible. As a
matter of fact, compression and computation are now recognised to be two
sides of the same coin, as they exploit the same underlying structure both
for storing and operating on data.
Despite numerous successes in the field, however, several challenges remain
open, including (but not limited to) extending techniques to more/less
structured and massive data. The goal of this Special Issue is precisely to
advance research in the field of compressed computation. We welcome
submission of high-quality papers dealing with compressed data structures,
data compression, string/tree/graph processing, and combinatorics.
The following topics will be the central (but not exclusive) themes of the
volume:
- Compressed data structures
- Data compression
- String and graph processing
- Combinatorics on strings and graphs
- Text indexing
- Pattern matching
More details for the special issue can be found at:
https://www.mdpi.com/journal/algorithms/special_issues/Compressed_Computation
Dr. Alberto Policriti
Dr. Nicola Prezza
Guest Editors
--
Nicola Prezza
Assistant Professor (research)
Dipartimento di Impresa e Management, Luiss Guido Carli, Roma
+39 0685225386
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