Seminar:
Applied Mathematics
Event time:
Wednesday, September 20, 2023 - 3:00pm
Location:
LOM 206
Speaker:
Neta Rabin
Speaker affiliation:
Tel-Aviv University
Event description:
Regression methods provide a simple mechanism for evaluating empirical functions over scattered data points, allowing to forecast future values. In particular, kernel-based regressions, such as the Nadaraya-Watson estimator are suitable for cases in which the relationship between the data points and the function is not linear. Successive applications of the Nadarya-Watson estimator, also known as Laplacian Pyramids model or iterative bias reduction, yield a multiscale model that generates a smoothed version of a function by using Gaussian kernels to smooth the residuals.
In this talk, I will review some recent extensions of this regression for spatio-temporal forecasting and bio-medical applications.