Incentive-based ledger protocols for solving machine learning tasks and optimization problems via competitions

David Amar, Lior Zilpa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We propose incentive-based protocols that use competitions and public ledgers to solve optimization problems. We introduce Proof-of-Accumulated-Work (PoAW): miners compete in costumer-submitted jobs and accumulate recorded work on which they are later remunerated. These new competitions replace the standard hash puzzle-based competitions. A competition is managed by a dynamically-created small masternode network (dTMN) of invested miners, which improves scalability as we do not need the entire network to manage the competition. Using a careful design of incentives, our system preserves security, avoids attacks, and offers new markets to the miners. Finally, we illustrate how the new protocols can be used for implementing machine learning competitions.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
PublisherIEEE Computer Society
Pages2838-2846
Number of pages9
ISBN (Electronic)9781728125060
DOIs
StatePublished - Jun 2019
Event32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 - Long Beach, United States
Duration: 16 Jun 201920 Jun 2019

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2019-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Country/TerritoryUnited States
CityLong Beach
Period16/06/1920/06/19

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