13 May 2020
Seminar, Lecture, Talk
MATH_PhD Student Seminar - Perfectly matched layer for optical modes
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.
13 May 2020
Seminar, Lecture, Talk
MATH_PhD Student Seminar - Computational Resolution Limit: a Modern View of a Classical Problem
Given an image generated by the convolution of point sources with a bandlimited function, the inverse problem is to reconstruct the source number, positions, and amplitudes. It is well-known that it is impossible to resolve the sources when they are close enough in practice.
13 May 2020
Seminar, Lecture, Talk
CHEM - PhD Student Seminar - Material Engineering in Thin-Film Transistor
Student: Mr. Chen HU
Department: Department of Chemistry, HKUST
Supervisor: Professor Shihe YANG
9 May 2020
Conference, Symposium, Forum
Symposium on Risk Management and Business Intelligence 2020 - Applying AI in Business
The Symposium on Risk Management and Business Intelligence 2020 will be held on 9 May 2020 (Saturday) afternoon by ZOOM.
8 May 2020
Seminar, Lecture, Talk
Seminar on Statistics and Data Science - Clustering via Uncoupled Regression (CURE)
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.
7 May 2020
Seminar, Lecture, Talk
Seminar on Data Science and Applied Mathematics - Partial Differential Equation Principled Trustworthy Deep Learning
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.
6 May 2020
Seminar, Lecture, Talk
PhD Student Seminar - Type II Theta Liftings on Loop Groups
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).
30 Apr 2020
Seminar, Lecture, Talk
Seminar on Data Science and Machine Learning - How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
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).
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