# Convex Optimization on Functionals of Probability Densities

arXiv: https://arxiv.org/abs/2002.06488 · HTML: https://mlsanity.com/paper/2002.06488/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2020.

## Built on by (most cited first, 3 of 3)

- [Energy-guided Entropic Neural Optimal Transport](https://mlsanity.com/paper/2304.06094/) (2023)
- [Symmetries in Overparametrized Neural Networks: A Mean-Field View](https://mlsanity.com/paper/2405.19995/) (2024)
- [Autoselection of the Ensemble of Convolutional Neural Networks with Second-Order Cone Programming](https://mlsanity.com/paper/2302.05950/) (2023)

## Abstract (arXiv)

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.