1 citations · 1 across the 5 of their papers we have counts for
5 papers
Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity
Zixuan Zhang, Kaixuan Huang, Tuo Zhao +2
Diffusion models have become a leading framework in generative modeling, yet their theoretical understanding -- especially for high-dimensional data concentrated on low-dimensional…
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization
Jiahui Cheng, Minshuo Chen, Hao Liu +2
Label Shift has been widely believed to be harmful to the generalization performance of machine learning models. Researchers have proposed many approaches to mitigate the impact of…
Differentially Private Estimation of Hawkes Process
Simiao Zuo, Tianyi Liu, Tuo Zhao +1
Point process models are of great importance in real world applications. In certain critical applications, estimation of point process models involves large amounts of sensitive pe…
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
Tianyi Liu, Yan Li, Enlu Zhou +1
We investigate the role of noise in optimization algorithms for learning over-parameterized models. Specifically, we consider the recovery of a rank one matrix $Y^*\in R^{d\times d…
Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network
Siawpeng Er, Edward Liu, Minshuo Chen +4
This paper presents a deep learning assisted synthesis approach for direct end-to-end generation of RF/mm-wave passive matching network with 3D EM structures. Different from prior…