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A Bregman Extension of quasi-Newton updates II: Convergence and Robustness Properties
A Bregman Extension quasi-Newton updates II Convergence Robustness Properties
2010/10/19
We propose an extension of quasi-Newton methods, and investigate the convergence and the robustness properties of the proposed update formulae for the approximate Hessian matrix. Fletcher has studied ...
Robustness and accuracy of methods for high dimensional data analysis based on Student's t statistic
Bootstrap central limit theorem classication dimension reduction higher criticism large deviation probability
2010/3/9
Student's t statistic is nding applications today that were never envisaged
when it was introduced more than a century ago. Many of these applications
rely on properties, for example robustness aga...
Bayesian robustness modelling using regularly varying distributions
Bayesian robustness heavy-tailed distributions conicting information regular variation credence
2009/9/21
Bayesian robustness modelling using heavy-tailed distributions pro-
vides a exible approach to resolving problems of conicts between the data and
prior distributions. See Dawid (1973) and OHaga (197...
Robustness of the Sequential Testing Procedures for the Feneralized Life Distributions
Robustness the Sequential Testing Procedures the Feneralized Life Distributions
2009/9/17
Robustness of the Sequential Testing Procedures for the Feneralized Life Distributions。
Robustness of multiple testing procedures against dependence
False-discovery rate family-wise error rate linear process moving average multiplicity significance level
2010/3/18
An important aspect of multiple hypothesis testing is controlling
the significance level, or the level of Type I error. When the test
statistics are not independent it can be particularly challengin...
Probabilistic Robustness Analysis——Risks，Complexity and Algorithms
Robustness analysis risk analysis randomized algorithms uncertain system computational complexity
2010/4/30
It is becoming increasingly apparent that probabilistic approaches
can overcome conservatism and computational complexity of the classical worstcase
deterministic framework and may lead to designs t...