114 citations · 256 across the 16 of their papers we have counts for
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cs.LG2024
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…
eess.SP2024
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…