Invention Grant
- Patent Title: Generating cross-domain data using variational mapping between embedding spaces
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Application No.: US15953986Application Date: 2018-04-16
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Publication No.: US10885111B2Publication Date: 2021-01-05
- Inventor: Subhajit Chaudhury , Sakyasingha Dasgupta , Asim Munawar , Ryuki Tachibana
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Randall Bluestone
- Main IPC: G06F16/84
- IPC: G06F16/84 ; G06N3/08

Abstract:
A computer-implemented method, computer program product, and system are provided for learning mapping information between different modalities of data. The method includes mapping, by a processor, high-dimensional modalities of data into a low-dimensional manifold to obtain therefor respective low-dimensional embeddings through at least a part of a first network. The method further includes projecting, by the processor, each of the respective low-dimensional embeddings to a common latent space to obtain therefor a respective one of separate latent space distributions in the common latent space through at least a part of a second network. The method also includes optimizing, by the processor, parameters of each of the networks by minimizing a distance between the separate latent space distributions in the common latent space using a variational lower bound. The method additionally includes outputting, by the processor, the parameters as the mapping information.
Public/Granted literature
- US20190318040A1 GENERATING CROSS-DOMAIN DATA USING VARIATIONAL MAPPING BETWEEN EMBEDDING SPACES Public/Granted day:2019-10-17
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