This Project Grant award of $600,000 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research at the Massachusetts Institute of Technology (MIT) to develop a mathematical foundation for using graph data in machine learning tasks. The goal is to create principled methods for exploiting the latent geometry and structure underlying graph data, such as from social networks or protein interaction networks, to improve machine learning...
The Massachusetts Institute of Technology (MIT) received a $600,000 Project Grant award from the National Science Foundation (NSF) on December 1, 2021 to fund research titled "COLLABORATIVE RESEARCH: FOUNDATIONS OF DEEP LEARNING: THEORY, ROBUSTNESS, AND THE BRAIN?" through November 30, 2024. The award is part of the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in these scientific fields and strengthen the national scientific...
This $1.2 million project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the Massachusetts Institute of Technology to develop new techniques for interactive machine learning with rich feedback. Over a three-year period from September 2022 to August 2025, the grantee will pursue three objectives: establishing a framework for grounding complex feedback using simple supervisory signals; creating algorithms allowing...
The Massachusetts Institute of Technology (MIT) received a $529,462 Project Grant award from the National Science Foundation (NSF) Division of Computing and Communication Foundations on June 1, 2021 to support research titled "COLLABORATIVE RESEARCH: CIF: MEDIUM: ANALYSIS AND GEOMETRY OF NEURAL DYNAMICAL SYSTEMS." The award is part of the NSF's Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education in...
The National Science Foundation Division of Information and Intelligent Systems awarded a $1.2 million Project Grant to the International Computer Science Institute of Berkeley, California from October 1, 2021 to September 30, 2025. The grant supports research under the Computer and Information Science and Engineering program (CFDA 47.070) to develop scalable second-order methods for training, designing, and deploying machine learning models. The CFDA program aims to advance computing and...
The Massachusetts Institute of Technology (MIT) received a $330,000 Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program. The grant supports research from 2023 to 2026 on non-parametric estimation techniques to address challenges with covariate shift in machine learning models. Specifically, MIT researchers will characterize fundamental limits of estimation with covariate shift, develop efficient algorithms that achieve these limits,...
The Massachusetts Institute of Technology (MIT) received a $531,494 Project Grant award from the National Science Foundation Division of Computing and Communication Foundations on May 1, 2023 to complete work by April 30, 2026. Under this award, MIT will conduct research investigating low-degree methods for optimization in random structures and their potential and limitations. Specifically, MIT aims to verify if low-degree method-based algorithms can achieve state-of-the-art performance across a...
This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research by the Texas A&M Engineering Experiment Station (Tees) to develop machine learning models for learning structural frameworks of an agent's dynamic decision-making behavior. The project aims to advance state-of-the-art methodologies for learning structural models of control by considering diverse data types, including...
The Massachusetts Institute of Technology (MIT) received a three-year $600,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) to develop algorithms that leverage structural properties in distribution testing. MIT will extend the reach of distribution testing through more efficient solutions that capitalize on known data structures. The university will also design sample-efficient methods to ascertain if data...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $599,963 to the University of Southern California (USC) for a 3-year research project focused on developing new mathematical and algorithmic frameworks to advance the understanding of machine learning. The key objectives of the project are to: (a) identify optimal algorithms and recipes for supervised machine learning, (b) explain the success of common...