Classification Protocols with Minimal Disclosure

• URL: http://arxiv.org/abs/2209.02690v1
• Date: Tue, 6 Sep 2022 17:57:52 GMT
• Title: Classification Protocols with Minimal Disclosure
• Authors: Jinshuo Dong, Jason Hartline, Aravindan Vijayaraghavan
• Abstract summary: We consider multi-party protocols for classification motivated by applications such as e-discovery in court proceedings. We identify a protocol that guarantees that the requesting party receives all responsive documents and the sending party discloses the minimal amount of non-responsive documents. This protocol can be embedded in a machine learning framework that enables automated labeling of points.
• Score: 12.308957254601243
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We consider multi-party protocols for classification that are motivated by applications such as e-discovery in court proceedings. We identify a protocol that guarantees that the requesting party receives all responsive documents and the sending party discloses the minimal amount of non-responsive documents necessary to prove that all responsive documents have been received. This protocol can be embedded in a machine learning framework that enables automated labeling of points and the resulting multi-party protocol is equivalent to the standard one-party classification problem (if the one-party classification problem satisfies a natural independence-of-irrelevant-alternatives property). Our formal guarantees focus on the case where there is a linear classifier that correctly partitions the documents.

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