6 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Stochastic Continuum Models for High-Entropy Alloys with Short Range Order
In this paper, we establish stochastic elastic model and stochastic Peierls--Nabarro (PN) model with short range order (SRO) in high--entropy alloys (HEAs).
6 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Overparametrized Model and Adversarial Robustness
Deep neural networks can predict well even when fitting noisy data. The phenomenon is called benign overfitting.
5 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Precision Matrix Estimation in Gaussian Graphical Model
In this era of big data, quantifying relationships between different components of a complex system is an appealing and challenging problem.
5 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - High-frequency trading with the order flow information
The development in computer technology have enabled computerized trading algorithms. Market making is one of the most famous high frequency trading strategy. By placing bid and ask orders simultaneously, market maker provides liquidity to the market.
5 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Decentralized Finance: Investment Aggregator and Portfolio Management System
The global blockchain technology market size is expected to expand at a compound annual growth rate of over 80% from 2021 to 2028.
5 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Split Knockoffs: towards Controlling Directional False Discovery Rate under Transformations
Multiple comparisons in hypothesis test are often subject to structural constraints in applications. In structural Magnetic Resonance Imaging for Alzheimer's Disease, one studies not only the atrophy brain regions, but also comparisons of anatomically adjacent regions.
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Integration of single-cell atlases with generative adversarial networks
As single-cell technologies evolved over years, diverse single-cell atlas datasets have been rapidly accumulated. Integrative analyses harmonizing such datasets provide opportunities for gaining deep biological insights.
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks
Pruning is a model compression method that removes redundant parameters and accelerates the inference speed of deep neural networks while maintaining accuracy. Most available pruning methods impose various conditions on parameters or features directly.
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