Recent discoveries in statistical inference for SPDEs
Due to the recent COVID-19 outbreak, this event has been cancelled. Speaker: Hyun-Jun Kim, visiting assistant professor of Applied Mathematics, ÂÌñÉç Description: In this talk, we discuss...
Due to the recent COVID-19 outbreak, this event has been cancelled. Speaker: Hyun-Jun Kim, visiting assistant professor of Applied Mathematics, ÂÌñÉç Description: In this talk, we discuss...
Speaker: Igor Cialenco, Associate Professor, Department of Applied Mathematics, Illinois Institute of Technology Description: We propose a novel methodology for estimation of risk capital allocation...
Speaker: Sergey Nadtochiy, Associate Professor, Department of Applied Mathematics, Illinois Institute of Technology Description: I will present a simple model of market microstructure which explains...
Speaker: Gregory Pasemann, TU Berlin Description: In this talk we consider drift estimation for Stochastic Partial Differential Equations (SPDEs). While Girsanov's theorem implies that the drift of a...
Speaker: Adrien Richou, associate professor, University of Bordeaux Event Topic: Stochastic Analysis
Speaker: Konstantin Makarychev, Associate Professor, Department of Computer Science, Northwestern University Description: We investigate dimensionality reduction for Euclidean kk-means and kk-medians...
Speaker: Albina Danilova, Visiting Associate Professor, Questrom School of Business, Boston University Description: The folk result in Kyle-Back models states that the value function of the insider...
Speaker: Mark Cerenzia, Dickson Instructor, Department of Mathematics, University of Chicago Description: Random matrix statistics emerge in a broad class of strongly correlated systems, with evidence...
Host Department of Applied Mathematics Speaker Andrew Papanicolau Tandon School of Engineering, New York University Description Principal component analysis (PCA) is a useful tool when trying to...
Speaker: Xiling Zhang, Postdoc, Department of Applied Mathematics, Illinois Institute of Technology Description: This project aims at finding a good approximation for the distribution of the iterated...