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通过选择性采样估计回归函数的极值和相关水平集

Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective Sampling
课程网址: http://videolectures.net/colt2013_minsker_estimation/  
主讲教师: Stanislav Minsker
开课单位: 杜克大学
开课时间: 2013-08-09
课程语种: 英语
中文简介:
我们提出了一种新方法,用于估计受随机噪声污染的观测值的函数绝对最大值(最小值)的位置和值。我们的目标是在最小的规律性和形状约束下解决问题。特别是,我们不假设函数的可微性,也不假设它的最大值在单个点上获得。我们为所提出的估计器的性能提供紧密的上限和下限。我们的方法适用于大类底层分布的问题的未知参数。
课程简介: We propose a new method for estimating the locations and the value of an absolute maximum (minimum) of a function from the observations contaminated by random noise. Our goal is to solve the problem under minimal regularity and shape constraints. In particular, we do not assume differentiability of a function nor that its maximum is attained at a single point. We provide tight upper and lower bounds for the performance of proposed estimators. Our method is adaptive with respect to the unknown parameters of the problem over a large class of underlying distributions.
关 键 词: 函数绝对最大值(最小值); 函数的可微性
课程来源: 视频讲座网
最后编审: 2019-03-10:mmx
阅读次数: 77