This National Science Foundation (NSF) Division of Information and Intelligent Systems Project Grant aims to advance "few-round active learning" algorithms and enable more efficient training of supervised machine learning models. The $300,000 award to Virginia Polytechnic Institute & State University (Virginia Tech), running from August 1, 2023 to July 31, 2026, will support research to: 1) develop methods for quantifying the utility of unlabeled data for active learning tasks, and 2) design algorithms that optimize this utility metric while improving it over a limited number of interaction rounds with human annotators. The project findings are expected to benefit a broad range of machine learning applications by reducing the time and cost of obtaining labeled training data. This award supports the NSF's Computer and Information Science and Engineering (CFDA 47.070) program, which funds investigator-initiated research and education across computing and information science domains.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $300.0k | 7/17/23 |