Processing of machine learning modeling data to improve accuracy of categorization

A system comprising:

• at least one programmable processor;
• and
• a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
• receiving, by a first multi-party computation (MPC) system of an MPC cluster and from an application on a client device, an inference request comprising a first share of a given user profile for a user of the application and a performance threshold;
• identifying, by performing a secure MPC process using a trained machine learning model in collaboration with one or more second MPC systems, a set of nearest neighbors to the user profile;
• selecting, from the set of nearest neighbors, one or more nearest neighbors having a performance measure that satisfies the performance threshold;
• and
• transmitting, by the first MPC system, data derived from the one or more nearest neighbors to the application.

One or more computer program products storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:

• receiving, by a first multi-party computation (MPC) system of an MPC cluster and from an application on a client device, an inference request comprising a first share of a given user profile for a user of the application and a performance threshold;
• identifying, by performing a secure MPC process using a trained machine learning model in collaboration with one or more second MPC systems, a set of nearest neighbors to the user profile;
• selecting, from the set of nearest neighbors, one or more nearest neighbors having a performance measure that satisfies the performance threshold;
• and
• transmitting, by the first MPC system, data derived from the one or more nearest neighbors to the application.