10 Oct 2025
Seminar, Lecture, Talk
IAS / School of Science Joint Lecture - Use of Large Animal Models to Investigate Brain Diseases
Abstract Genetically modified animal models have been extensively used to investigate the pathogenesis of age-dependent neurodegenerative diseases, such as Alzheimer (AD), Parkinson (PD), Huntington (HD) diseases, and Amyotrophic Lateral Sclerosis (ALS). The common feature of these diseases…
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29 Apr 2021
Seminar, Lecture, Talk
MATH - PhD Student Seminar - Adversarial Defense with Self-supervised Test-time Fine-tuning
Current neural networks can be easily attacked by small artificially chosen noise called adversarial examples.
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29 Apr 2021
Seminar, Lecture, Talk
CHEM - PhD Student Seminar - Design, Characterization and Applications of Persistent Organic Radicals
Student: Mr. Han YU Department: Department of Chemistry, HKUST Supervisor: Professor He YAN
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29 Apr 2021
Seminar, Lecture, Talk
MATH - PhD Student Seminar - Private Federated Learning
In this seminar, we will discuss private federated learning. We will firstly provide new optimization error bounds for differential private federated learning with Laplacian Smoothing (DP-Fed-LS) and heterogeneous data.
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29 Apr 2021
Seminar, Lecture, Talk
CHEM - PhD Student Seminar - Crystal Modifier – Mechanism and Medical Application
Student: Mr. Jiatao MAO Department: Department of Chemistry, HKUST Supervisor: Professor Qing CHEN
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28 Apr 2021
Seminar, Lecture, Talk
IAS / SSCI Joint Lecture - Glass-Based Advanced Mid-Infrared Photonic Devices
For Attendees' Attention: This lecture will be held on-site at LT-K and online via zoom.
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28 Apr 2021
Seminar, Lecture, Talk
MATH - Seminar on Pure Mathematics - The Physics and Mathematics of BCOV Theory
In this talk, I will first introduce the mirror symmetry for Calabi-Yau threefolds, which describes the genus zero structures of the Gromow-Witten theory.
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26 Apr 2021
Seminar, Lecture, Talk
IAS / SSCI Joint Lecture - Computation with Tensor Networks
Abstract
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22 Apr 2021
Seminar, Lecture, Talk
MATH - Seminar on Data Science and Applied Math - Explore the Compressible Gradients in High-Dimensional Zeroth-Order Optimization
We consider the problem of minimizing an objective function without any derivative information. Such optimization is called zeroth-order, derivative-free, or black-box optimization.
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