CCMA Seminar on Mathematics of Data and Computation

This CCMA seminar aims to introduce cutting-edge research of numerical methods and scientific computing related to data science and machine learning and are held weekly on every Thursday 8:00-9:00 pm EST (Friday 8:00-9:00 am Beijing time). If you want to give a talk, please contact Xiaofeng Xu(xkx5060@psu.edu).

(Due to the COVID-19, we move all the seminars online, ZOOM: https://psu.zoom.us/j/99704506940)

 

Date Room Speaker Title
January 20, 2022 Zoom Jongho Park Additive Schwarz methods for convex optimization—convergence theory and acceleration
January 27, 2022 Zoom Zhonghua Qiao Maximum bound principle preserving integrating factor Runge–Kutta methods for semilinear parabolic equations
February 3, 2022 Zoom Jia Zhao Physics-informed Computational Modeling of Multiphase Complex Fluids with Applications in Life Science
February 10, 2022 Zoom TBA
February 17, 2022 Zoom TBA
February 24, 2022 Zoom Li Jiang Explore the faster training algorithm for logistic regression
March 3, 2022 Zoom TBA
March 10, 2022 Zoom Arnulf Jentzen Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning
March 17, 2022 Zoom TBA
March 24, 2022 Zoom Juncai He Side-effects of Learning from Low Dimensional Data Embedded in an Euclidean Space
March 31, 2022 Zoom Haizhao Yang Discretization-invariant operator learning: algorithms and theory
April 7, 2022 Zoom TBA
April 14, 2022 Zoom Julián David Gutiérrez Pineda The potential method for price-formation mean-field games via Recurrent Neural Nets”
April 21, 2022 Zoom TBA
April 28, 2022 Zoom Shangyou Zhang Superconvergent conforming discontinuous Galerkin finite elements
May 5, 2022 Zoom Yeonjong Shin Active Neuron Least Squares: A Training Method for Rectified Neural Networks
May 12, 2022 Zoom TBA TBA
May 19, 2022 https://psu.zoom.us/j/99704506940 TBA
May 26, 2022 https://psu.zoom.us/j/99704506940 TBA
June 9, 2022 https://psu.zoom.us/j/99704506940 TBA
June 16, 2022 https://psu.zoom.us/j/99704506940 TBA

 

Past seminars

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