5 citations · 7 across the 5 of their papers we have counts for
5 papers
Generalized energy and gradient flow via graph framelets
Andi Han, Dai Shi, Zhiqi Shao +1
In this work, we provide a theoretical understanding of the framelet-based graph neural networks through the perspective of energy gradient flow. By viewing the framelet-based mode…
A Discussion On the Validity of Manifold Learning
Dai Shi, Andi Han, Yi Guo +1
Dimensionality reduction (DR) and manifold learning (ManL) have been applied extensively in many machine learning tasks, including signal processing, speech recognition, and neuroi…
Coupling Matrix Manifolds and Their Applications in Optimal Transport
Dai Shi, Junbin Gao, Xia Hong +2
Optimal transport (OT) is a powerful tool for measuring the distance between two defined probability distributions. In this paper, we develop a new manifold named the coupling matr…
Asymptotic Joint Distribution of Extreme Eigenvalues of the Sample Covariance Matrix in the Spiked Population Model
Dai Shi
In this paper, we consider a data matrix where all the columns are i.i.d. samples being dimensional complex Gaussian of mean zero and covariance $Σ…
Smallest Gaps Between Eigenvalues of Random Matrices With Complex Ginibre, Wishart and Universal Unitary Ensembles
Dai Shi, Yunjiang Jiang
In this paper we study the limiting distribution of the smallest gaps between eigenvalues of three kinds of random matrices -- the Ginibre ensemble, the Wishart ensemble and th…