Project Grant DESC0025453

This National Science Foundation project grant of $362,015 supports research into developing more fine-grained algorithms under the Computer and Information Science and Engineering program. The University of California, San Diego will conduct this research from November 2021 to January 2023. Specifically, the awardee will build a unified theory of designing fast approximation algorithms and study their fine-grained computational hardness. They will develop systematic techniques emphasizing...

The University of Chicago received a three-year, $120,000 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program to develop a cyberinfrastructure for randomized linear algebra algorithms. The cyberinfrastructure will enable rapid prototyping and reproducible testing of randomized algorithms to solve computationally intensive problems in scientific and engineering domains. It will include modular computational kernels, frameworks for benchmarking...

Rutgers University was awarded a three-year $540,000 Project Grant 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 grant will support Rutgers' development of efficient and deterministic methods for solving low-dimensional linear programs with floating-point precision. Key activities include designing scalable solvers that can handle both full-rank and...

This $300,000 project grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research on the query complexity of linear algebra problems. The overarching goal is to develop more efficient algorithms for solving core matrix problems, such as systems of linear equations and eigenvalue computations, which have widespread applications across machine learning, scientific computing, and engineering. The research...

This National Science Foundation project grant of $199,968 supports collaborative research at Tufts University from September 2022 through August 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The research aims to advance theory and computation for structured sensing problems involving low-rank matrix recovery from deterministically structured measurements. Specifically, the project will study scalable non-convex optimization methods for generalized matrix completion...

This National Science Foundation project grant of $250,000 will fund research at Rensselaer Polytechnic Institute from July 2022 to June 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports the development of accelerated distributed stochastic optimization methods and applications in machine learning. Specifically, the grantee will design fast-convergent and communication-efficient optimization algorithms with theoretical guarantees for solving...

This two-year, $251,672 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support research into non-smooth and non-Lipschitz Riemannian optimization methods. The grantee, Rice University, will study algorithmic approaches such as the manifold alternating direction method of multipliers and inertial manifold proximal gradient method to develop new tools for solving important classes of non-convex optimization...

This three-year, $200,000 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program will fund the development of more computationally efficient methods for solving high-dimensional problems that commonly arise in scientific, engineering, and commercial computing. Specifically, the grant recipient, Stanford University, will improve randomized quasi-Monte Carlo sampling techniques and develop a median-of-means strategy to better handle problems involving large...

This Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences federal grant program (CFDA 47.049), provides $201,419 to the Research Foundation of the City University of New York (RFCUNY) on behalf of Bernard M. Baruch College. The award will support research focused on improving quantitative bounds for foundational results in additive combinatorics, number theory, commutative algebra, and algebraic geometry that rely on...

This Project Grant from the National Science Foundation Division of Mathematical Sciences provides $225,000 in funding to the University of California, San Diego from September 1, 2022 to August 31, 2025. The award supports research advancing the basic understanding of outliers in the spectra of random networks, which can be used to deduce various network properties and have applications in machine learning, bioinformatics, and coding theory. The principal investigator will study general network...