This Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $1,127,925 to Carnegie Mellon University for research titled "Foundations of Self-Supervised Learning through the Lens of Probabilistic Generative Models." The research aims to develop scientific and mathematical foundations for self-supervised learning by analyzing aspects of deep generative models that can be recovered through self-supervised learning. It also seeks to understand relative advantages of self-supervised learning methods versus other probabilistic model learning approaches from both statistical and algorithmic perspectives. This work will help address current challenges in self-supervised learning methodology design and evaluation, with the goal of advancing accessibility and inclusiveness of machine learning technologies. The award period is from October 1, 2022 through September 30, 2026.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $1.1m | 8/25/22 |