Exact minimax strategies for predictive density estimation, data compression and model selection Export

@proceedings{citeulike:1576521, abstract = {The Bayes procedure with uniform prior on location (and log-scale) parameters is shown to be exact minimax optimal for location and scale families in problems of universal data compression, predictive density estimation and model selection.}, author = {Liang, Feng and Barron, A. R.}, booktitle = {Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on}, citeulike-article-id = {1576521}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1023421}, journal = {Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on}, keywords = {bayes, information-ball, kullback-leibler, minimax}, pages = {149+}, posted-at = {2007-08-20 10:50:18}, priority = {2}, title = {Exact minimax strategies for predictive density estimation, data compression and model selection}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1023421}, year = {2002} }

TY - CONF ID - citeulike:1576521 L3 - citeulike-article-id:1576521 N2 - The Bayes procedure with uniform prior on location (and log-scale) parameters is shown to be exact minimax optimal for location and scale families in problems of universal data compression, predictive density estimation and model selection. JF - Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on TI - Exact minimax strategies for predictive density estimation, data compression and model selection T2 - Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on SP - 149 KW - bayes KW - information-ball KW - kullback-leibler KW - minimax AU - Liang, Feng AU - Barron, AR PY - 2002/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1023421 ER -