Given any finite set of integer points S, there is an associated function f_S that encodes S, which we call its integer point transform. One can think of this integer […]
CCMS Colloquium invites you to a talk by Sinai Robins (University of São Paulo - Brazil) Title: An introduction to the geometry of numbers through the lens of analysis Abstract: […]
Please join us for a career discussion with three great panelists: Sireesh Vinnakota - Graduate Student at UCI Luke Trujillo - Senior Software Engineer at Operant AI Michelle Goodwin - […]
Abstract: Earlier work has shown that similarity-based predictive models can improve upon predictive performance, as compared to using the entire training data to help build models, particular regarding model discrimination for binary responses. My collaborators and I have some updated results to share, regarding similarity-based modeling for joint consideration of model calibration and discrimination, as […]
The Riemann–Hilbert correspondence relates algebra to differential equations on complex algebraic varieties. In characteristic p, there is an analogous correspondence due to Emerton–Kisin and later generalized by Bhatt–Lurie, where the […]
We welcome all undergraduate/graduate students and faculty to attend topology seminar! Speaker: Puttipong Pongtanapaisan (Pitzer College) Title: Special Positions of Shapes in Four-Dimensional Space Abstract: I will begin by convincing you that four-dimensional space is more familiar than it might first appear. Then, I will introduce ways in which mathematicians study objects in 4-space. Each […]
CCMS Colloquium invites you to a talk by Braxton Osting (University of Utah) Title: Blood pressure monitoring with biophysics-informed machine learning models Abstract: Measurement of blood pressure (BP) is essential for early diagnosis and management of hypertension, a condition that 45% of US adults have and a risk factor for development of heart failure, the […]
Abstract: Modern machine learning is ultimately a simple process: We iteratively update the weights of machine learning models to minimize a problem-specific loss. When it works well, we deploy the model in human-facing domains like healthcare, finance, or the justice system. But even though we know how models are trained, we don't understand why they […]
It is a fundamental question to find rational solutions to a given system of polynomials, and in modern language this translates into finding rational points in algebraic varieties. It is […]
CCMS Colloquium invites you to a talk by Anna Ma (UCI) Title: Stochastic iterative methods for solving tensor linear systems Abstract: Solving linear systems is a crucial subroutine and challenge in data science and scientific computing. Classical approaches for solving linear systems assume that data is readily available and small enough to be stored in […]
This GEMS session will be facilitated by Grace Akinwande from the Claremont Graduate University. Title: From Pizza to Calculus: Understanding Area Through Approximation Abstract: How much more pizza do you […]
Abstract: Anderson Acceleration (AA) has been widely used to solve nonlinear fixed-point problems due to its rapid convergence. This talk focuses on a variant of AA in which multiple Picard […]
