114 citations · 256 across the 16 of their papers we have counts for
16 papers
H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction
Zhexi Gu, Jiaxin Ying, Xu-Wen Wang +1
Accurate prediction of physician referral links is essential for optimizing care coordination and reducing fragmentation in healthcare delivery. However, existing computational met…
Time-Varying Graph Learning for Data with Heavy-Tailed Distribution
Amirhossein Javaheri, Jiaxi Ying, Daniel P. Palomar +1
Graph models provide efficient tools to capture the underlying structure of data defined over networks. Many real-world network topologies are subject to change over time. Learning…
Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals
Andrei Buciulea, Jiaxi Ying, Antonio G. Marques +1
This paper introduces Polynomial Graphical Lasso (PGL), a new approach to learning graph structures from nodal signals. Our key contribution lies in modeling the signals as Gaussia…
Learning Large-Scale MTP Gaussian Graphical Models via Bridge-Block Decomposition
Xiwen Wang, Jiaxi Ying, Daniel P. Palomar
This paper studies the problem of learning the large-scale Gaussian graphical models that are multivariate totally positive of order two (). By introducing the concep…
Network Topology Inference with Sparsity and Laplacian Constraints
Jiaxi Ying, Xi Han, Rui Zhou +2
We tackle the network topology inference problem by utilizing Laplacian constrained Gaussian graphical models, which recast the task as estimating a precision matrix in the form of…
A Fast and Provable Algorithm for Sparse Phase Retrieval
Jian-Feng Cai, Yu Long, Ruixue Wen +1
We study the sparse phase retrieval problem, which seeks to recover a sparse signal from a limited set of magnitude-only measurements. In contrast to prevalent sparse phase retriev…