Spectral Sparsifier: A sparse graph that approximates the spectral (eigenvalue) properties of the Laplacian matrix of the original graph.

We give a survey of graph spectral techniques used in computer sciences. The survey consists of a description of particular topics from the theory of graph spectra independently of the areas of ...

Using spectral sparsification, the researchers ran many algorithms in a sparse graph, and obtained approximately the correct results as well.

In this paper, we study the spectral radius of bipartite graphs. Let 𝐺 be a bipartite graph with 𝑒 edges without isolated vertices. It was known that the spectral radius of 𝐺 is at most the square ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Using spectral sparsification, the researchers ran many algorithms in a sparse graph, and obtained approximately the correct results as well. This general framework allowed them to speed up the ...

According to his MIT profile, John Urschel is focused on spectral graph theory, numerical linear algebra and machine learning.

MIMO networks are emerging as a key B5G/6G technology for improved connectivity, spectral efficiency, and service quality. A ...