5 papers
An Uncertainty-Aware Generalization Framework for Cardiovascular Image Segmentation
Ting Yu Tsai, Liangqiao Gui, Yineng Chen +8
Deep learning models have achieved significant success in segmenting cardiovascular structures, but there is a growing need to improve their generalization and robustness. Current…
Integral-Operator-Based Spectral Algorithms for Goodness-of-Fit Tests
Shiwei Sang, Shao-Bo Lin, Xuehu Zhu
The widespread adoption of the \emph{maximum mean discrepancy} (MMD) in goodness-of-fit testing has spurred extensive research on its statistical performance. However, recent studi…
Feature Qualification by Deep Nets: A Constructive Approach
Feilong Cao, Shao-Bo Lin
The great success of deep learning has stimulated avid research activities in verifying the power of depth in theory, a common consensus of which is that deep net are versatile in…
Integral Operator Approaches for Scattered Data Fitting on Spheres
Shao-Bo Lin
This paper focuses on scattered data fitting problems on spheres. We study the approximation performance of a class of weighted spectral filter algorithms, including Tikhonov regul…
Component-based Sketching for Deep ReLU Nets
Di Wang, Shao-Bo Lin, Deyu Meng +1
Deep learning has made profound impacts in the domains of data mining and AI, distinguished by the groundbreaking achievements in numerous real-world applications and the innovativ…