Accession Number:

AD1168006

Title:

Multi-View Relationships for Analytics and Inference

Descriptive Note:

[Technical Report, Doctoral Thesis]

Corporate Author:

Carnegie Mellon University

Personal Author(s):

• Lei, Eric

Report Date:

2019-08-01

Pagination or Media Count:

148

Abstract:

An interesting area of machine learning is methods for multi-view data, relational data whose features have been partitioned. Multi-view learning exploits relationships between views, giving it certain advantages over traditional single-view techniques, which may struggle to find these relationships or only learn them implicitly. These relationships are often especially salient in understanding the data or performing prediction.

Descriptors:

• computational science
• data mining
• information science
• network science
• information processing
• neural networks
• data science
• bayesian networks
• mathematical filters
• cardiovascular physiological phenomena
• supervised machine learning
• surveys
• information systems
• machine learning
• statistical algorithms
• artificial intelligence software
• automata theory

Subject Categories:

• Optical Detection and Detectors

Distribution Statement:

[A, Approved For Public Release]