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Princeton University

International Conference on Statistical Foundations of Data Science and their Applications will be held at Princeton University in May 8-10, 2023. The conference will bring together collaborators and leading researchers in statistics and data science. The conference will provide an excellent forum for scientific communications and promote collaborations among researchers in statistics and data science. The program covers a wide range of topics presenting recent developments and the state of the art in a variety of modern research topics on statistics and data science as well as their applications.

Information & Knowledge Management, Big Data Computing,    Scientific Computing and Data Science

ICERM

This workshop will focus on the intersection of mathematics, statistics, machine learning, and computation, when viewed through the lens of optimal transport (OT). Mathematical topics will include low-dimensional models for OT, linearizations of OT, and the geometry of OT including gradient flows and gradient descent in the space of measures. Relevant statistical topics will include reliable and efficient estimation of OT plans in high dimensions, the role of regularization in computing OT distances and plans, with applications to robust statistics, uncertainty quantification, and overparameterized machine learning. Computation will be a recurring theme of the workshop, with emphasis on the development of fast algorithms and applications to computational biology, high energy physics, material science, spatio-temporal modeling, natural language processing, and image processing.

Program Staff;     Phone: [1-401-863-5030];     Email: programstaff@icerm.brown.edu

Scientific Computing and Data Science,    Numerical Analysis and Computational Mathematics

Mathematical Sciences Research Institute (MSRI)

The goal of the summer school is for the students to first become familiar with the concept of concentration of measure in different settings (Euclidean, Riemannian and discrete), and the main open problems surrounding it. The students will later become familiar with the proof techniques that involve the different types of localization and obtain expertise on the ways to apply the localization techniques. After attending the graduate school, the students are expected to have the necessary background that would give them a chance to both conduct research around open problems in concentration of measure, find new applications to existing localization techniques and perhaps also develop new localization techniques.

Courses and Events for Math Students and Early Career Researchers,    Geometry and Topology

American Nuclear Society (ANS)

Since 1978, the ANS biennial topical conference on Probabilistic Safety Assessment has been a worldwide forum for communication of major probabilistic risk and safety topics, including issues, methods, applications, insights, policy, research, and risk-informed regulation experience. PSA 2023 will be of interest to those working in traditional applications such as nuclear reactor facilities, nonreactor installations, processing, decontamination & decommissioning, storage as well as other nontraditional areas where probabilistic safety approaches are applied.

Eastern North American Region International Biometric Society (ENAR)

American Statistical Association

American Statistical Association

American Statistical Association (ASA)