%0 Journal Article %1 6654274 %A Nielsen, F. %A Nock, R. %D 2014 %J IEEE Signal Processing Letters %K approximate divergences entropy %N 1 %P 10-13 %R 10.1109/LSP.2013.2288355 %T On the chi square and higher-order chi distances for approximating f-divergences %U https://ieeexplore.ieee.org/abstract/document/6654274 %V 21 %X We report closed-form formula for calculating the Chi square and higher-order Chi distances between statistical distributions belonging to the same exponential family with affine natural space, and instantiate those formula for the Poisson and isotropic Gaussian families. We then describe an analytic formula for the f-divergences based on Taylor expansions and relying on an extended class of Chi-type distances.

@article{6654274, abstract = {We report closed-form formula for calculating the Chi square and higher-order Chi distances between statistical distributions belonging to the same exponential family with affine natural space, and instantiate those formula for the Poisson and isotropic Gaussian families. We then describe an analytic formula for the f-divergences based on Taylor expansions and relying on an extended class of Chi-type distances.}, added-at = {2019-12-11T14:51:53.000+0100}, author = {{Nielsen}, F. and {Nock}, R.}, biburl = {https://www.bibsonomy.org/bibtex/2a43ca0464055d7434560766a2efeaad2/kirk86}, description = {On the chi square and higher-order chi distances for approximating f-divergences - IEEE Journals & Magazine}, doi = {10.1109/LSP.2013.2288355}, interhash = {3087cfb276b0e4f31862ccc15e3a6a20}, intrahash = {a43ca0464055d7434560766a2efeaad2}, issn = {1558-2361}, journal = {IEEE Signal Processing Letters}, keywords = {approximate divergences entropy}, month = jan, number = 1, pages = {10-13}, timestamp = {2019-12-11T14:51:53.000+0100}, title = {On the chi square and higher-order chi distances for approximating f-divergences}, url = {https://ieeexplore.ieee.org/abstract/document/6654274}, volume = 21, year = 2014 }