Project Grant 2207457
- The National Science Foundation awarded University of California Irvine a $499,793 Project Grant under the federal Computer and Information Science and Engineering grant program (CFDA 47.070). The grant will support the development of brain-inspired machine learning algorithms to provide real-time feedback to sensors and intelligently control data generation rates. This is expected to reduce sensor data outputs by up to four orders of magnitude for applications in infrastructure, mobile devices,...
- The National Science Foundation awarded a $219,999 Project Grant under the Engineering program (CFDA 47.041) to the University of California, Davis for research titled "CCSS: COLLABORATIVE RESEARCH: QUALITY-AWARE DISTRIBUTED COMPUTATION FOR WIRELESS FEDERATED LEARNING: CHANNEL-AWARE USER SELECTION, MINI-BATCH SIZE ADAPTATION, AND SCHEDULING." The award period is from October 1, 2021 through July 31, 2024. The research will develop techniques for channel-aware user selection, mini-batch...
- The National Science Foundation (NSF) Directorate for Engineering (CFDA #47.041) awarded a $360,000 Project Grant to the University of California, Irvine (UC Irvine) to develop advanced "neurally-inspired" technology for seamlessly integrating communication and machine learning. The key products and services to be delivered under this 3-year grant are: (1) Designing rigorous communication schemes that leverage redundant and holographic neural representations to achieve...
- The University of California Irvine received a $299,999 National Science Foundation Project Grant under the Engineering federal grant program (CFDA 47.041) for work on "HYPERDIMENSIONAL NEURAL COMPUTATION FOR REAL-TIME COGNITIVE LEARNING." The grant period runs from September 15, 2021 through August 31, 2024 in Irvine, California. The NSF Engineering program seeks to improve quality of life and economic strength by fostering innovation and excellence in engineering research and...
- 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,...
- This two-year, $368,179 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) funds research on developing innovative edge learning algorithms over wireless multi-access channels. Specifically, the University of California, Davis is collaborating with Arizona State University to take a principled approach to edge learning framework design using gradient-based and gradient-free optimization methods under computing, power, and...
- The National Science Foundation awarded a $525,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) to support research investigating energy-efficient persistent learning-in-memory with quantum tunneling dynamic synapses from October 1, 2022 to September 30, 2025. The award will fund the development of novel learning hardware and software tools to significantly improve the energy efficiency of artificial...
- The National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) awarded a $472,000 Project Grant to the Regents of the University of Minnesota, a non-profit 1862 land grant college, to develop a general framework for designing and analyzing decentralized and federated learning systems. The proposed work aims to unify various distributed algorithms and provide insights to streamline their design and analysis across a range of applications beyond machine learning, such as control...
- Project Grant Summary The National Science Foundation's Division of Electrical, Communications and Cyber Systems awarded $433,114 to the University of California, Irvine under the Engineering program (CFDA 47.041) for a three-year project (October 1, 2025–September 30, 2028) focused on developing distributed algorithms for submodular maximization under matroid constraints. The primary deliverable is a suite of practical distributed optimization algorithms with analytically characterized...
- This $299,889 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research at the University of California, San Diego (UCSD) to develop algorithms for compressing and improving the efficiency of large neural networks used in modern artificial intelligence applications. The key products and services to be delivered include: The research project focuses on developing quantization, pruning, and low-rank...
The National Science Foundation awarded a $420,000 Project Grant to the University of California Irvine under the Engineering federal grant program (CFDA 47.041) for work spanning September 1, 2022 to August 31, 2025. The award funds research to design distributed and quantized kernel-based learning algorithms over interconnected sensing systems without transmitting collected data over networks. Specifically, the university will develop online distributed and quantized kernel-based learning methods involving local updates communicated between neighboring nodes, enabling networks to collectively learn global models across static and dynamic architectures. The researchers will formally present different distributed and quantized function learning algorithms and study their performance, convergence, and regret analysis for various network structures accounting for delays and dynamics. Additionally, the university will design adaptive distributed and quantized algorithms and examine optimal resource allocation tradeoffs between computation accuracy and network resources. The goal is robust distributed and quantized kernel learning algorithms less sensitive to network characteristics like topology and delays.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $420.0k | 8/30/22 |