Semantics preservation for machine learning models deployed as dependent on other machine learning models

• Main Authors: Godfrey, Edouard, Wang, Kuangyu, Fasoli, Gianpaolo
• Format: Patent
• Language: English
• Published: 01.08.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

The subject technology receives assessment values determined by a first machine learning model deployed on a client electronic device, the assessment values being indicative of classifications of input data and the assessment values being associated with constraint data that comprises a probability distribution of the assessment values with respect to the classifications of the input data. The subject technology applies the assessment values determined by the first machine learning model to a second machine learning model to determine the classifications of the input data. The subject technology determines whether accuracies of the classifications determined by the second machine learning model conform with the probability distribution for corresponding assessment values determined by the first machine learning model. The subject technology retrains the first machine learning model when the accuracies of the classifications determined by the second machine learning model do not conform with the probability distribution.