Information geometry of statistical inference - an overview
暂无分享,去创建一个
[1] John D. Lafferty,et al. Boosting and Maximum Likelihood for Exponential Models , 2001, NIPS.
[2] Kenji Fukumizu,et al. Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons , 2000, Neural Computation.
[3] Giovanni Pistone,et al. The Exponential Statistical Manifold: Mean Parameters, Orthogonality and Space Transformations , 1999 .
[4] Shun-ichi Amari,et al. Statistical inference under multiterminal rate restrictions: A differential geometric approach , 1989, IEEE Trans. Inf. Theory.
[5] Shun-ichi Amari,et al. Information geometry of Boltzmann machines , 1992, IEEE Trans. Neural Networks.
[6] Shun-ichi Amari,et al. Natural Gradient Works Efficiently in Learning , 1998, Neural Computation.
[7] Shun-ichi Amari,et al. Information geometry on hierarchy of probability distributions , 2001, IEEE Trans. Inf. Theory.
[8] S. Amari,et al. Information geometry of estimating functions in semi-parametric statistical models , 1997 .
[9] Shun-ichi Amari,et al. Information geometry of turbo and low-density parity-check codes , 2004, IEEE Transactions on Information Theory.