【摘 要】
：
Problems that require estimating high-dimensional matrices from noisy and/or incomplete observations arise frequently in statistics.Examples include dimensi
【机 构】
：
DepartmentofStatistics,UCBerkeleyBerkeley,CaliforniaUSA
【出 处】
：
The Third IMS-China International Conference on Statistics a
论文部分内容阅读
Problems that require estimating high-dimensional matrices from noisy and/or incomplete observations arise frequently in statistics.Examples include dimensionality reduction methods (e.g., principal components and canonical correlation),collaborative filtering and matrix completion (e.g., Netflix and other recommender systems), multivariate regression, estimation of time-series models, and graphical model learning, When the sample size is less than the matrix dimensions, all of these problems are ill-posed, so that some type of structure is required in order to obtain interesting results.
其他文献
For high-dimensional classification, it is well known that naively performing the Fisher discriminant rule leads to poor results due to diverging spectra (B
为了适应房地产开发经营业务发展的需要 ,进一步规范房地产开发企业财务行为 ,加强房地产开发企业财务管理 ,现将财政部《关于印发〈房地产开发企业财务管理若干问题的补充规
The space of positive definite symmetric matrices has been studied extensively as a means of understanding dependence in multivariate data along with the ac
本文在文献[1]的基础上,针对分布式环形网的环境,对文献[1]所给算法加以改进,并论证了改进算法的正确性及其在性能方面的优越性.
Based on the literature [1], this paper
为了解定西市安定区城乡居民生活饮用水质量,确保饮用水安全、卫生达标,对定西市安定区部分地方的生活饮用水进行水质常规分析项目的测定。从检测的12个水质指标可以看出,安
目的探讨农村家庭聚餐预防食物中毒的有效途径。方法对一起农村聚餐食物中毒调查,分析农村家宴的食品安全隐患。结果农村家宴制作存在从业人员缺乏管理、食品采购把关不严、
Functional Data Analysis (FDA) aims to develop statistical methods for collections of curves, surfaces, etc.Such functional data come from observations of f
We consider clustering problems involving functional data where we have a collection of functions, each viewed as a process realization, e.g., a random curv
Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model.It chooses an equilibrium with a sparse regr
Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations,but is better described by fractional diffusion models