- Conference Paper
We present an approximation method to a class of parametric integration problems that naturally appear when solving the dual of the maximum entropy estimation problem. Our method builds up on a recent generalization of Gauss quadratures via an infinite-dimensional linear program, and utilizes a convex clustering algorithm to compute an approximate solution which requires reduced computational effort. It shows to be particularly appealing when looking at problems with unusual domains and in a multi-dimensional setting. As a proof of concept we apply our method to an example problem on the unit disc. Show more
Book title20th IFAC World Congress. Proceedings
Journal / seriesIFAC-PapersOnLine
Pages / Article No.
SubjectEntropy maximization; convex clustering; linear programming; importance sampling
Organisational unit03751 - Lygeros, John / Lygeros, John
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