Convex Optimization on Functionals of Probability Densities
arXiv:2002.06488v26 citations
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This work provides theoretical insights for researchers in information theory, but it is incremental as it focuses on conditions and uniqueness without introducing new methods or broad applications.
The paper addresses convex optimization problems on strictly convex functionals of probability densities in information theory, establishing conditions for minimizers and proving uniqueness when a minimizer exists.
In information theory, some optimization problems result in convex optimization problems on strictly convex functionals of probability densities. In this note, we study these problems and show conditions of minimizers and the uniqueness of the minimizer if there exist a minimizer.