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iDASH is a competition soliciting implementations of cryptographic schemes ofinterest in the context of biology. In 2019, one track asked for multi-partycomputation implementations of training of a machine learning model suitablefor two datasets from cancer research. In this note, we describe our solutionsubmitted to the competition. We found that the training can be run on threeAWS c5.9xlarge instances in less then one minute using MPC tolerating onesemi-honest corruption, and less than ten seconds at a slightly lower accuracy.

A Note on Our Submission to Track 4 of iDASH 2019