Divergence measures for statistical data processing—An annotated bibliography -
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This paper provides an overview of results and concepts in minimax robust hypothesis
testing for two and multiple hypotheses. It starts with an introduction to the subject …

We consider a family of divergence-based minimax approaches to perform robust filtering.
The mismodeling budget, or tolerance, is specified at each time increment of the model …

In this article, we consider a robust state-space filtering problem in the case that the
transition probability density is unknown and possibly degenerate. The resulting robust filter …

Tseng's algorithm finds a zero of the sum of a maximally monotone operator and a
monotone continuous operator by evaluating the latter twice per iteration. In this paper, we …

We study optimal transport-based distributionally robust optimization problems where a
fictitious adversary, often envisioned as nature, can choose the distribution of the uncertain …

We introduce a distributionally robust minimium mean square error estimation model with a
Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The …

A robust fixed-lag smoothing approach is proposed in the case there is a mismatch between
the nominal model and the actual model. The resulting robust smoother is characterized by …

This paper considers robust filtering for a nominal Gaussian state-space model, when a
relative entropy tolerance is applied to each time increment of a dynamical model. The …

The full potential of multi-input multi-output (MIMO) communication systems relies on
exploiting channel state information at the transmitter (CSIT), which is, however, often …