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Abstract In this paper, we study characterizations of differentiability for real-valued functions based on generalized differentiation. These characterizations provide the mathematical foundation for Nesterov's smoothing techniques in infinite dimensions. As… Click to show full abstract
Abstract In this paper, we study characterizations of differentiability for real-valued functions based on generalized differentiation. These characterizations provide the mathematical foundation for Nesterov's smoothing techniques in infinite dimensions. As an application, we provide a simple approach to image reconstructions based on Nesterov's smoothing and algorithms for minimizing differences of convex (DC) functions that involve the regularization.
Keywords:
difference convex;
convex functions;
techniques difference;
smoothing techniques;
image reconstructions
Journal Title: Optimization
Year Published: 2019
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Journal Title: Optimization
Year Published: 2019
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!