Divergence measures for statistical data processing—An annotated bibliography -
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Estimation of the ratio of probability densities has attracted a great deal of attention since it
can be used for addressing various statistical paradigms. A naive approach to density-ratio …

This is the first comprehensive book on information geometry, written by the founder of the
field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide …

Artificial intelligence (AI) has historically been conceptualized in anthropomorphic terms.
Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital …

In this paper, we extend and overview wide families of Alpha-, Beta-and Gamma-
divergences and discuss their fundamental properties. In literature usually only one single …

This book gives a comprehensive account of density-based minimum distance methods and
their use in statistical inference. It covers statistical distances, density-based minimum …

In the practice of point prediction, it is desirable that forecasters receive a directive in the
form of a statistical functional. For example, forecasters might be asked to report the mean or …

What are the natural loss functions or fitting criteria for binary class probability estimation?
This question has a simple answer: so-called “proper scoring rules”, that is, functions that …

In this paper we consider robust parameter estimation based on a certain cross entropy and
divergence. The robust estimate is defined as the minimizer of the empirically estimated …

Controlling a device with a brain-computer interface requires extraction of relevant and
robust features from high-dimensional electroencephalographic recordings. Spatial filtering …