Project Grant 2312840

Award Date 7/1/23
Completion Date 6/30/26
Dollars Obligated $400K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Columbus, OH 43210, USA
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The National Science Foundation (NSF), through its Computer and Information Science and Engineering program (CFDA 47.070), has awarded a $400,000 project grant to The Ohio State University to conduct research on the theoretical principles underlying the success of deep learning models. The 3-year award, effective July 1, 2023, will focus on three main thrusts:

  1. Developing a unified mathematical framework to analyze the convergence and neural collapse properties of overparameterized deep learning models trained on general loss functions.

  2. Leveraging the structure of neural collapse to derive tighter generalization bounds for deep learning models.

  3. Exploring how the generalization of neural collapse can be used to understand and improve the transferability of deep models to new domains and tasks.

This research aims to advance the fundamental theoretical understanding of deep learning and yield practical insights for improving model performance, generalization, and transferability. The project also includes an integrated outreach and education plan to promote awareness of computing and STEM concepts for K-12 students.

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