Classifying Big Data over Networks via the Logistic Network Lasso
We apply network Lasso to solve binary classification (clustering) problems on network structured data. To this end, we generalize ordinary logistic regression to non-Euclidean data defined over a complex network structure. The resulting logistic network Lasso classifier amounts to solving a non-smooth convex optimization problem. A scalable classification algorithm is obtained by applying the alternating direction methods of multipliers to solve this optimization problem.
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