An Active Learning Methodology for Design and Optimization of Complex Expensive Tests

Abstract

Advance capabilities for design and optimization of complex and expensive tests through development, verification, and validation of new mathematical and statistical models within the framework of active learning in data mining. Formulations will lead to new learning methodologies for more efficient testing in order to reduce the number of required testing with improved statistical properties.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 15, 2016
Source ID
FA95501610171

Entities

People

  • Adel Alaeddini

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Texas at San Antonio

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Fluid Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms