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Trustless Machine Learning Contracts; Evaluating and Exchanging Machine Learning Models on the Ethereum Blockchain

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arxiv 1802.10185 v1 pith:KVFIXLDI submitted 2018-02-27 cs.CR

classification cs.CR
keywords learningmachineblockchaincontractsmodelssoftwareagentsreward
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Using blockchain technology, it is possible to create contracts that offer a reward in exchange for a trained machine learning model for a particular data set. This would allow users to train machine learning models for a reward in a trustless manner. The smart contract will use the blockchain to automatically validate the solution, so there would be no debate about whether the solution was correct or not. Users who submit the solutions won't have counterparty risk that they won't get paid for their work. Contracts can be created easily by anyone with a dataset, even programmatically by software agents. This creates a market where parties who are good at solving machine learning problems can directly monetize their skillset, and where any organization or software agent that has a problem to solve with AI can solicit solutions from all over the world. This will incentivize the creation of better machine learning models, and make AI more accessible to companies and software agents.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Trustable and Automated Machine Learning Running with Blockchain and Its Applications

    cs.LG 2019-08 reject novelty 4.0 of 10

    A compact binary model format is proposed for edge scoring, and a Capsule Network based synthetic-data generator is claimed to improve fraud detection with limited training data.

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