This Project Grant award, valued at $180,803, was provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to The Administrators of Tulane Educational Fund, doing business as Tulane University. The award will fund a research project to study a class of machine learning algorithms known as Deep Learning, which has important societal applications such as self-driving cars and virtual assistants. The key goals...
This four-year, $1.2 million project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new efficient and scalable distributed learning algorithms and frameworks. The grantee, Michigan State University, will systematically investigate computation and communication efficiency challenges in centralized and decentralized machine learning paradigms. Researchers will address these issues through three research directions to...
This $131,520 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports research to advance decentralized learning methods. The project, led by William Marsh Rice University, aims to address fundamental challenges related to communication efficiency, data heterogeneity, and algorithmic complexity in decentralized learning systems. The research is structured around three main thrusts: 1) designing finite-time...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance artificial intelligence (AI) by investigating the mathematical foundations and practical applications of deep learning models. The research focuses on understanding the properties of neural networks trained on large datasets, how these properties enable the modeling of complex data distributions, and the principles underlying...
This $131,959 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research conducted by Rutgers, The State University to develop new deep learning training methods that can efficiently scale to utilize high-performance computing (HPC) systems. The key goals are to: 1) Explore techniques like second-order information approximation, computation-communication tradeoffs, and data compression to enhance the speed...
Purdue University was awarded a $299,742 Project Grant from the National Science Foundation Division of Computing and Communication Foundations. The grant falls under the Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education in computing, communications, and information science and engineering. The grant will fund a collaborative research project titled "FET: MEDIUM: NEUROPLANE: SCALABLE DEEP LEARNING THROUGH...
This $400,000 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a principled and unified mathematical framework for deep learning on low-dimensional data structures. The project aims to bridge the gap between theory and practice of deep learning by designing "white-box" deep neural networks using unrolled optimization schemes to maximize information gain in...
This $598,448 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports a research project that develops theoretical and algorithmic foundations for online learning and decision-making involving sequential data under unknown stochastic models. The project has three main thrusts: (1) developing representation learning for nonlinear and nonparametric time series models, (2) advancing statistical...
Purdue University was awarded a $450,000 project grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) to advance trustworthy reinforcement learning techniques for online decision making. The three-year award beginning August 15, 2022 will support research into robustness, fairness, causality and explainability in dynamic pricing, dynamic assortment selection and two-sided market matching. The University will develop new theoretical tools,...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $391,848 to Purdue University to develop holistic systems for securing the machine learning supply chain. The project aims to create tools to quantify trust in machine learning supply chains and verify security requirements across those supply chains. The research will also support the development of a diverse next generation of computer...