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Tokenized Data Markets

1 Pith paper cite this work. Polarity classification is still indexing.

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abstract

We formalize the construction of decentralized data markets by introducing the mathematical construction of tokenized data structures, a new form of incentivized data structure. These structures both specialize and extend past work on token curated registries and distributed data structures. They provide a unified model for reasoning about complex data structures assembled by multiple agents with differing incentives. We introduce a number of examples of tokenized data structures and introduce a simple mathematical framework for analyzing their properties. We demonstrate how tokenized data structures can be used to instantiate a decentralized, tokenized data market, and conclude by discussing how such decentralized markets could prove fruitful for the further development of machine learning and AI.

fields

cs.CR 1

years

2019 1

verdicts

UNVERDICTED 1

representative citing papers

Secure Computation in Decentralized Data Markets

cs.CR · 2019-07-02 · unverdicted · novelty 4.0

Secure multi-party computation protocols are proposed for arbitrary computations on decentralized data markets, with reported performance on two healthcare applications.

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Showing 1 of 1 citing paper.

  • Secure Computation in Decentralized Data Markets cs.CR · 2019-07-02 · unverdicted · none · ref 13 · internal anchor

    Secure multi-party computation protocols are proposed for arbitrary computations on decentralized data markets, with reported performance on two healthcare applications.