INTELLIGENCE-DRIVEN LEARNING
Abstract
The research objective of this proposal is to investigate implications and applications of the proposed Composite Learning approach that targets the synergy of knowledge-based and data-based methods of machine learning while realizing that synergy as intelligent fusion of distinct components towards achieving state-of-the-art performance with robustness to traditional natural data vulnerabilities and novel adversarial challenges. The anticipated outcome of proposed Composite Learning research will include- (1) Exploring applicability of the proposed approach to calibration machine learning problems. (2) Narrowing the gap between machine learning models in terms of their sensitivity to both natural and malicious data corruption.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502210200
Entities
People
- Vladimir Vapnik
Organizations
- Air Force Office of Scientific Research
- Trustees of Columbia University in the City of New York
- United States Air Force