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Explores irreducible matrices and strong connectivity in networked control systems, emphasizing the importance of adjacency matrices and graph structures.
Explores consensus algorithms in networked control systems, covering topics like Metropolis-Hasting models and distributed computation of Least-Squares regression.
Covers the k-Nearest-Neighbor classifier, hand-written digit recognition, multi-class k-NN, data reduction, applications, graph construction, limitations, and the curse of dimensionality.
