The versatility of exponential families, along with their attendant convexity properties, make them a popular and effective statistical model. A central issue is learning these mo...
We develop an analog of the exponential families of Wilf in which the label sets are finite dimensional vector spaces over a finite field rather than finite sets of positive integ...
Presentation of the exponential families, of the mixtures of such distributions and how to learn it. We then present algorithms to simplify mixture model, using Kullback-Leibler di...
The exponential embedding of two or more probability density functions (PDFs) is proposed for multimodal sensor processing. It approximates the unknown PDF by exponentially embedd...
When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the co...