Concept and Context Bi-Hierarchical Learning

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$69,985.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
N00014-11-M-0493
Award Id:
n/a
Agency Tracking Number:
N102-175-1113
Solicitation Year:
2010
Solicitation Topic Code:
N102-175
Solicitation Number:
2010.2
Small Business Information
19 Whitney Avenue, New Haven, CT, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
030077908
Principal Investigator:
Frederick Warner
Vice President
(203) 285-8617
warner@plainsightsystems.com
Business Contact:
Andreas Coppi
Vice President
(203) 285-8617
coppi@plainsightsystems.com
Research Institution:
Stub




Abstract
Synthesizing a variety of ideas and algorithms from Machine Learning, Kernel methods, Spectral Graph Theory, Diffusion Geometries, Harmonic Analysis and Signal Processing into a single mathematical framework, we propose a data driven processing toolbox capable of generating bi-hierarchical information organization and prediction (models) essential for analytical data organization. The associated empirical models are also complemented by natural extensions of all quantities measured on the known data to new data. This extension methodology leads to automatic invariant feature or language definitions and to regression and analysis of empirical functions on and off the data. These resulting algorithms yield a powerful system for automatic learning and classification that is essentially data agnostic and requires no specific ab initio knowledge.

* information listed above is at the time of submission.

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