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Interactive Generative Manifold Learning

Award Information

Department of Defense
Award ID:
Program Year/Program:
2013 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
11600 Sunrise Valley Drive Suite # 210 Reston, VA 20191-
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2013
Title: Interactive Generative Manifold Learning
Agency: DOD
Contract: N00014-13-M-0022
Award Amount: $79,982.00


Exploratory data analysis is the foremost step in selecting appropriate statistical learning algorithms specialized to a dataset. We have proposed a generative framework for visualizing high dimensional data as low-dimensional manifold embedded in a high dimensional space. The method allows user to conveniently explore the space using fewer dimensions while still capturing the principal modes of variations of the high dimensional data. Specifically, we employ Gaussian Process Latent Variable Model (GPLVM) and Spectral Latent Variable Model (SLVM) to learn low-dimensional representations of the data. Probabilistic mappings between the embeddings and the original space facilitate efficient interpolation in the latent space as well as fast visualization of the interpolated latent points in the original space. To allow the user to span the manifold in an intuitive manner, we develop supervised and semi-supervised tools to relate the latent space to the meaningful feature space. These enable computation of principle direction for each point in the latent space to allow the user to traverse in a meaningful way. Further, we have proposed a principled approach to extrapolate the latent space by predicting the manifold structure in regions lying outside the existing domain of the data.

Principal Investigator:

Ping Wang
Principal Investigator
(703) 654-9352

Business Contact:

Paul Brewer
VP, New Technology
(703) 725-3084
Small Business Information at Submission:

11600 Sunrise Valley Drive Suite # 210 Reston, VA 20191

EIN/Tax ID: 541969286
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No