Belief Propagation on Graphs

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Explores non-parametric regression for networks, covering object data analysis, network graphs, extrinsic distances, and practical projections.

Explores the Cavity Method in Mean Field Theory, analyzing spins in an external field within a graph.

Explores the concept of minimizing guardians in graphs through strategic edge selection.

Explains message passing in graphical models and the matching problem in graph theory.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Explores maximizing diversity in document selection, graph clique determination, theorems on negative type, and convex optimization.

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Introduces the probabilistic method to prove existence results in graph theory.

Covers polynomial identity testing using oracles and random point evaluation, with applications in graph theory and algorithmic aspects.

Explores graph theory, stochastic matrices, consensus algorithms, and spectral properties in networked control systems.