The Regents of the University of California, doing business as University of California, Berkeley, received a $483,663 Project Grant award from the National Science Foundation Division of Computing and Communication Foundations under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will support research from June 15, 2023 through May 31, 2026 to develop theoretically grounded algorithms and analyze sample complexity for partially observable...
This $398,856 National Science Foundation project grant supports research at Northwestern University to improve reinforcement learning algorithms. Specifically, the grant funds the development of sample-efficient and computationally-efficient algorithms for both online and offline reinforcement learning with function approximation. The researchers aim to incorporate optimistic exploration and pessimistic exploitation techniques using faithful uncertainty quantification for neural networks....
The National Science Foundation awarded a $600,000 Project Grant to Princeton University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research toward developing a mathematical foundation for deep reinforcement learning over the period from October 1, 2022 to September 30, 2026. Specifically, the project aims to bridge current gaps in theoretical reinforcement learning and deep neural networks by investigating guarantees achievable by...
This $600,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program will support research at Stanford University toward developing a mathematical foundation for deep reinforcement learning. Over four years, the grant will fund three research thrusts investigating the types of guarantees achievable by reinforcement learning policies under different problem structures and increasing neural network complexity. The researchers will also...
The National Science Foundation Division of Information and Intelligent Systems awarded a $1.2 million Project Grant to the International Computer Science Institute of Berkeley, California from October 1, 2021 to September 30, 2025. The grant supports research under the Computer and Information Science and Engineering program (CFDA 47.070) to develop scalable second-order methods for training, designing, and deploying machine learning models. The CFDA program aims to advance computing and...
This $800,000 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant, awarded to the University of California, Berkeley on October 1, 2024, funds research to develop methods for certifying the safety of autonomous systems that use machine learning components. The key objectives are: (1) learning safety certificates and control policies, and (2) certifying the learned system. The project aims to use learning-based techniques to compute...
The National Science Foundation Division of Information and Intelligent Systems awarded a $500,000 Project Grant to Stanford University from October 1, 2021 to September 30, 2024. The grant supports research titled "USING AND GATHERING DATA FOR EFFICIENT BATCH REINFORCEMENT LEARNING" under the Computer and Information Science and Engineering program (CFDA 47.070). This three-year Project Grant will fund research at Stanford University to develop techniques for using and gathering...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program Project Grant (CFDA 47.070) of $151,593 awarded to Cornell University on March 1, 2024 will support the development of new reinforcement learning (RL) algorithms that can learn efficiently and reliably from limited training data. The key products of this 5-year project will be RL algorithms that can be safely deployed in real-world applications like autonomous driving and generative AI where...
This $474,000 federal Project Grant award, issued by the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070), supports research to develop neural bandit learning algorithms that leverage deep learning techniques to optimize decision-making in contexts with incomplete feedback. The primary awardee, the University of California, Los Angeles (UCLA), will lead a multi-year research project to bridge the gap between deep learning...
The National Science Foundation awarded $800,000 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the University of California, San Diego from September 1, 2022 to August 31, 2025. The project grant funding will support the development of lifelong learning algorithms using hyperdimensional computing, a brain-inspired framework for distributed computing. Specifically, the awardee will advance algorithms for similarity search, density estimation,...