Invention Grant
- Patent Title: Latent space harmonization for predictive modeling
-
Application No.: US15367729Application Date: 2016-12-02
-
Publication No.: US10923213B2Publication Date: 2021-02-16
- Inventor: Nicolo Fusi , Jennifer Listgarten , Gregory Byer Darnell
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G16B40/00
- IPC: G16B40/00 ; G06N7/00 ; G16B40/20 ; G06N20/00

Abstract:
In embodiments of latent space harmonization (LSH) for predictive modeling, different training data sets are obtained from different measurement methods, where input data among the training data sets is quantifiable in a common space but a mapping between output data among the training data sets is unknown. A LSH module receives the training data sets and maps a common supervised target variable of the output data to a shared latent space where the output data can be jointly yielded. Mappings from the shared latent space back to the output training data of each training data set are determined and used to generate a trained predictive model. The trained predictive model is useable to predict output data from new input data with improved predictive power from the training data obtained using various, otherwise incongruent, measurement techniques.
Public/Granted literature
- US20180157794A1 Latent Space Harmonization for Predictive Modeling Public/Granted day:2018-06-07
Information query