We develop the method of perfectly matched layer (PML) for the calculation of optical modes in microcavities. The PML is constructed by implementing the complex coordinate transformation in the far field region.

Traditional human face genome-wide association studies (GWASs) are limited by small sample size and inefficient landmarks-based phenotyping methods.

The Symposium on Risk Management and Business Intelligence 2020 will be held on 9 May 2020 (Saturday) afternoon by ZOOM.

In this talk, we first consider a canonical clustering problem where one receives unlabeled samples drawn from a balanced mixture of two elliptical distributions and aims for a classifier to estimate the labels.

This talk contains two parts: In the first part, I will present some recent work on developing partial differential equation principled robust neural architecture and optimization algorithms for robust, accurate, private, and efficient deep learning.

We discuss the computation of some theta liftings of type II dual pairs for loop groups. We will focus on the simplest case of the pair (GL_1, GL_1).

A recent breakthrough in deep learning theory shows that the training of over-parameterized deep neural networks (DNNs) can be characterized by the neural tangent kernel (NTK).