The National Science Foundation (NSF) awarded a $225,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Leland Stanford Junior University. The 3-year grant, effective July 1, 2024, aims to gain a deeper theoretical understanding of the statistical properties of neural networks, which have revolutionized science and engineering. Key research directions include studying the distinguishing features of deep neural networks compared to classical statistical...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
This $300,000 National Science Foundation project grant supports research into robust machine learning under sparse adversarial attacks through 2025. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the University of California, Santa Barbara will develop theoretical frameworks and defense methods to make machine learning models resilient against perturbations affecting few data points. Specifically, the researchers aim to establish fundamental limits of...
The University of Florida was awarded a $125,701 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant will support the development of a mathematical foundation for novel artificial intelligence learning algorithms with applications to biology and engineering. Specifically, researchers will establish a theoretical framework for the minimax optimization of machine learning...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $250,000 Project Grant to the University of Central Florida (UCF) under the Mathematical and Physical Sciences program (CFDA 47.049). The three-year grant, effective August 1, 2023 through July 31, 2026, supports research to develop extensions and analytical techniques for Generalized Dot Product Graph (GDPG) network models, with a focus on applications in brain science, medical research, molecular biology,...
The National Science Foundation Division of Computing and Communication Foundations awarded a $500,000 Project Grant to Princeton University from January 1, 2022 to December 31, 2024 to support collaborative research on probabilistic, geometric, and topological analysis of neural networks. This award falls under the Mathematical and Physical Sciences program (CFDA 47.049), which aims to strengthen the Nation's scientific enterprise through advancing knowledge and understanding of major problems....
This $175,000 two-year project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at Old Dominion University Research Foundation to advance secure deep learning systems. The awardee will systematically study existing neural network backdoor attacks to understand fundamental attack principles. Based on these findings, the research team will develop algorithms to accurately detect neural backdoors embedded in deep learning...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $201,337 to San Diego State University Foundation to investigate fundamental aspects of deep neural network robustness and efficiency. The project aims to advance computational approaches, algorithms, and educational initiatives that address performance, efficiency, and robustness in deep learning systems. Key focus areas include developing a novel...
This $298,450 National Science Foundation project grant supports research to quantify the error landscape of deep neural networks. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the awardee New York University will employ statistical mechanics methods to characterize the basins of attraction in high-dimensional parameter spaces of deep learning models. The university will measure basin volume distributions and flatness as a function of network parameters...
The National Science Foundation (NSF) awarded a $402,229 Computer and Information Science and Engineering (CISE) Program grant to The Research Foundation For The State University Of New York, doing business as Stony Brook University. This 1-year grant, effective November 1, 2023, supports research and development focused on improving the security of machine learning (ML) systems that leverage third-party, pre-trained models. The project aims to develop rigorous methods for detecting and...