Project Grant N000142612067

This three-year Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program will support the development of new optimization approaches for machine learning problems. The $600,000 award to the University of Wisconsin-Madison beginning October 1, 2022 will advance optimization algorithms and analysis techniques for convex-concave minimax problems incorporating sparsity or regularity....

This $349,427 CAREER grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at The Leland Stanford Junior University (Stanford University) to develop machine learning (ML) techniques to improve the performance of discrete optimization algorithms. The project aims to address challenges in efficiently solving complex combinatorial optimization problems, such as those encountered in supply chain logistics and...

The National Science Foundation (NSF) awarded a $500,000 Project Grant to Northwestern University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of application-specific integrated circuit (ASIC) prototypes that leverage complementary metal-oxide semiconductor (CMOS) circuits integrated with voltage-controlled magnetic memory devices to enable probabilistic computing. The key products to be delivered through this 3-year project...

This Project Grant award of $263,764 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program supports research to address fundamental challenges in optimization algorithms, including those used for artificial intelligence (AI) and scientific computing. The project aims to develop new techniques to enable faster and more accurate optimization algorithms than currently possible. The key research thrusts include: (1) understanding the...

This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research on algorithms for optimization problems with uncertain or incomplete data inputs. The $484,600 grant awarded to the Regents of the University of Michigan will fund the design and analysis of parallelizable algorithms for stochastic optimization, as well as algorithms for stochastic optimization with unknown probability...

This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund a $174,965 project at the College of William & Mary in Williamsburg, Virginia. The project, titled "CRII: III: REINFORCEMENT LEARNING FOR COMBINATORIAL OPTIMIZATION IN SOCIETAL PROBLEMS," aims to develop innovative artificial intelligence (AI) technologies to efficiently solve complex real-world combinatorial optimization...

This $211,135 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to expand and improve the use of stochastic simulation models for optimal decision-making under uncertainty. The award, with a performance period from July 2024 to June 2027, will enhance the SIMOPT testbed of simulation optimization problems and solvers, making it more powerful, widely applicable, and aligned...

This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $600,000 to the University of Michigan to develop a new analytical method for analyzing large-scale stochastic systems from July 2022 to June 2025. The method aims to obtain non-asymptotic performance bounds for stochastic networks and systems using Lyapunov drift analysis combined with ideas from Stein's method, dimensionality reduction, and reproducing kernel Hilbert...

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...

The National Science Foundation awarded a $250,000 Project Grant to Lehigh University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to support collaborative research titled "A UNIFIED FRAMEWORK FOR ANALYZING ADAPTIVE STOCHASTIC OPTIMIZATION METHODS BASED ON PROBABILISTIC ORACLES" from January 15, 2022 through December 31, 2024. The grant funding will support Lehigh University, along with any relevant sub-awardees, in conducting...