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RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts...
The goal of network clustering algorithms is to detect dense clusters in a network, which provides a first step towards the understanding of large scale biological networks. With numerous recent advan...
We evaluate three population size estimators, including the post-stratification and lo-gistic regression estimators which has been or will be implemented in the US Census dual system surveys. Conditio...
Policies for the joint identification and control of uncertain systems are presented. The discussion focuses on the case of a multiple input, single output linear system, with no dynamics and quadrati...
The focus of this paper is to develop a framework for distributed estimation via convex optimization. We deal with a network of complex sensor subsystems with local estimation and signal processing. M...
We describe a specialized truncated Newton primal-dual interior-point method that solves large scale network utility maximization problems, with concave utility functions, efficiently and reliably. Ou...
We describe graph implementations, a generic method for representing a convex function via its epigraph, described in a disciplined convex programming framework. This simple and natural idea allows a ...
Minimum variance beamforming, which uses a weight vector that maximizes the signal to interference plus noise ratio (SINR), is often sensitive to estimation error and uncertainty in the parameters, st...
This paper concerns a fractional function of the form x^Ta/sqrt{x^TBx}, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, and choosing (a,B)...
We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is...
稳健主成分回归(RPCR)是稳健主成分分析和稳健回归分析结合使用的一种方法,本文首次运用稳健的RPCR及异常值诊断方法,对2008年我国地区经济增长横截面数据可靠性做了评估。评估结果表明:稳健的RPCR方法能更好地克服异常值的影响,使估计结果更加可靠,并能有效地克服经典的主成分回归(CPCR)方法容易出现的多个异常点的掩盖现象;基本可以认为2008年地区经济增长与相关指标数据是匹配的,但部分地区的...
基于稳健主成分回归的统计数据可靠性评估方法(下)。
统计数据质量是统计工作的生命,统计数据质量的高低直接关系到各类经济主体和政府部门对经济形势的判断和决策。文章借鉴全面质量管理的思想,从满足用户和统计数据产生全过程的角度,系统地阐述了统计数据质量的内涵,在此基础上提出构建我国政府统计数据质量评价体系的设想,以期为相关决策部门提供参考。
数据挖掘是在数据库中对数据进行一定的处理,从而获得其中隐含、事先未知的而又可能极为有用的信息。这些信息通常是以知识、规则或约束等形式来表现。这些知识可以用于知识管理、问题求解、制定决策、过程控制和其他领域。本文分析了数据挖掘技术的相关领域及其基本问题,为知识获取提供了一种新方法。
本文从数据挖掘技术谈起,结合证券行业的特点和实际应用,提出并分析证券行业需求,并针对“客户”这个主题,给出了证券行业数据仓库解决方案,提出了数据挖掘在证券行业中的应用。

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