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Structured Convex Optimization under Submodular Constraints
A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints.
Minimum Average Cost Clustering
In this paper, we introduce the minimum average cost criterion, and show that the theory of intersecting submodular functions can be used for clustering with submodular objective functions.
Submodularity Cuts and Applications
Several key problems in machine learning, such as feature selection and active learning, can be formulated as submodular set function maximization.
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