#6137. Overview of accurate coresets

October 2026publication date
Proposal available till 10-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Computer Science (all);
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
2350 $1200 $1050 $900 $
Contract №6137.1 Contract №6137.2 Contract №6137.3 Contract №6137.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

Abstract:
A coreset of an input set is its small summarization, such that solving a problem on the coreset as its input, provably yields the same result as solving the same problem on the original (full) set, for a given family of problems. Coresets have been suggested for many fundamental problems, for example, in machine/deep learning, computer vision, databases, and theoretical computer science. This introductory paper was written following requests regarding the many inconsistent coreset definitions, lack of source code, the required deep theoretical background from different fields, and the dense papers that make it hard for beginners to apply and develop coresets. The article provides folklore, classic, and simple results including step-by-step proofs and figures, for the simplest (accurate) coresets. Nevertheless, we did not find most of their constructions in the literature. Moreover, we expect that putting them together in a retrospective context would help the reader to grasp current results that usually generalize these fundamental observations. Experts might appreciate the unified notation and comparison table for existing results. Open source code is provided for all presented algorithms, to demonstrate their usage, and to support the readers who are more familiar with programming than mathematics.
Keywords:
big data mining; computational geometry; coresets; data summarization; machine learning

Contacts :
0