Learning with Submodular Functions: A Convex Optimization Perspective
Learning with Submodular Functions: A Convex Optimization Perspective
Submodular functions are relevant to machine learning for at least two reasons: (1) some problems may be expressed directly as the optimization of submodular functions, and (2) the Lovász extension of submodular functions provides a useful set of regularization functions for supervised and unsupervised learning. In Learning with Submodular Functions: …