Shuang Liang

I am a PhD student in the Statistics Department at UCLA. I work on mathematical theory of deep learning.

I am very fortunate to be advised by Guido Montúfar.

liangshuang at g.ucla.edu / Google scholar / Short CV

My current research focuses on optimization in neural networks. I aim to better understand:

The optimization trajectory in parameter space;
The implicit bias of the optimization algorithm (which model the algorithm tends to select);
How these aspects are influenced by network architecture, optimizer, initialization, step size, etc.

Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression.
Shuang Liang, Guido Montúfar. ICLR 2025 (Spotlight). Preprint [arXiv:2410.03988]. Virtual poster [SlidesLive].
Pull-back Geometry of Persistent Homology Encodings.
Shuang Liang, Renata Turkeš, Jiayi Li, Nina Otter, Guido Montúfar. TMLR 2024. Preprint [arXiv:2310.07073]. Repo [GitHub]. Video [Video].

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