Project Grant 2533814
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $275,000 to Carnegie Mellon University to develop and evaluate algorithms for cooperative learning across heterogeneous edge network devices. The key objectives are to: Extend existing theoretical work on online learning to settings with multiple heterogeneous agents facing different decision choices and privacy constraints, and develop algorithms...
- The National Science Foundation (NSF) awarded a $599,410 Project Grant to Carnegie Mellon University (CMU) to develop a collaborative learning framework for dynamic and diverse computing environments, particularly focused on edge devices. The grant, under NSF's Computer and Information Science and Engineering program (CFDA 47.070), aims to innovate model-parallel collaborative learning by designing unique model architectures and efficient algorithms, facilitate practical on-device training and...
- The National Science Foundation (NSF) awarded a $175,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the Board of Trustees of Southern Illinois University for the "CRII:OAC:UNITED LEARNING: DATA-SHAREABLE HETEROGENEOUS DISTRIBUTED LEARNING" project. This project aims to develop distributed learning systems that enable data sharing across heterogeneous computing devices, including personal computers, smartphones, and Internet of...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $249,998.00 to the University of Massachusetts to conduct collaborative research on developing corruption-robust online optimization and learning algorithms. The goal is to design learning algorithms that are both theoretically sound and practical to implement, enabling more robust decision-making in real-world applications...
- This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering (CFDA 47.070) program, provides $274,648 to Clemson University to develop heterogeneous architectures for collaborative machine learning. The research aims to address key challenges in efficiency, adaptivity, and privacy preservation when deploying collaborative machine learning models across diverse hardware platforms. The project will design specialized neural network...
- This Project Grant award, valued at $150,000.00, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The project aims to develop a novel Next Generation (NextG) network design to support resilient Federated Learning (FL) over large-scale heterogeneous mobile devices. Key technical objectives include: Exploiting serverless computing at the network edge to provide resilient and efficient ML...
- This federal Project Grant award of $165,874.00 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The award is for a collaborative research project titled "Scalable Learning from Distributed Data for Wireless Network Management - The Transition to 5G" led by The Johns Hopkins University. The research aims to develop scalable machine learning-based analytics to better manage and control next-generation...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award, with a total funding of $174,770, supports the development of an adaptive, federated, continuous learning system that uses a novel federated, semi-supervised learning framework. This framework aims to retrain deep neural network models on distributed, unlabeled, heterogeneous data from edge devices, while leveraging explainable AI techniques to expedite local training. The...
- This federal Project Grant award of $236,099 was provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, which supports fundamental and applied research across computational domains. The research aims to develop robust optimization and learning algorithms capable of handling dynamic and uncertain data scenarios, advancing our understanding of learning in modern machine learning environments. Key objectives include enhancing supervised...
- The National Science Foundation (NSF) awarded a $299,993 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Chicago. The grant supports a collaborative research project on the "Foundations of Few-Round Active Learning" in supervised machine learning. The key objectives are to advance active learning algorithms and improve understanding of their capabilities in scenarios with limited interaction rounds. The research aims...
This is a Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The $275,000 award supports research to develop cooperative online learning algorithms that allow multiple heterogeneous devices to collaboratively explore a large decision space and identify optimal solutions in computer network applications. The project aims to extend existing theory on online learning to settings with heterogeneous agents facing different decision choices and privacy constraints. The research will be applied to two network applications: distributed placement of computing applications across devices, and optimization of wireless resource allocation. The project also includes educational and outreach initiatives to introduce students to cooperative learning in networks. The award is held by the University of Massachusetts in Amherst and is scheduled to run from Oct 1, 2025 to Sep 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $275.0k | 7/31/25 |