Statistical Machine Learning with Restrictions on Shape, Structure and Computation
Abstract
The research carried out in this project is targeted at advancing the mathematical foundations of data science, by developing theory" and methodology for problems that have not been studied in traditional statistical and machine learning approaches. The research wi"ll develop models, theories and algorithms that can help scientists and engineers conduct more effective data analysis. The focus of"" the project is on statistical machine learning problems that impose restrictions on the computational resources consumed, or on the"" shape of estimators such as convexity and monotonicity. In addition, mathematical problems in graph-structured signal processing wi"ll be studied. A fourth area of investigation will be the use of statistical learning in optimization and scientific computing. The" potential relevance to Navy interests involves any domain where data processing is central, including sensing, tracking, communicat"ion and information management tasks.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 29, 2017
- Source ID
- N000141712925
Entities
People
- John D. Lafferty
Organizations
- Office of Naval Research
- United States Navy
- Yale University