搜索结果: 256-270 共查到“知识库 统计核算理论”相关记录323条 . 查询时间(3.109 秒)
Algorithmic and Statistical Perspectives on Large-Scale Data Analysis
Algorithmic Statistical Perspectives Large-Scale Data Analysis
2010/10/19
In recent years, ideas from statistics and scientific computing have begun to interact in increasingly sophisticated and fruitful ways with ideas from computer science and the theory of algorithms to...
Approximating a geometric fractional Brownian motion and related processes via discrete Wick calculus
discrete Wick calculus fractional Brownian motion weak convergence
2010/10/19
We approximate the solution of some linear systems of SDEs driven by a fractional Brownian motion $B^H$ with Hurst parameter $H\in(\frac{1}{2},1)$ in the Wick--It\^{o} sense, including a geometric fra...
A bagging SVM to learn from positive and unlabeled examples
A bagging SVM learn from positive unlabeled examples
2010/10/14
We consider the problem of learning a binary classifier from a training set of positive and unlabeled examples, both in the inductive and in the transductive setting. This problem, often referred to a...
Analysis of 24-Hour Ambulatory Blood Pressure Monitoring Data using Orthonormal Polynomials in the Linear Mixed Model
Cubic Spline DASH Study Graphical Display
2010/10/19
The use of 24-hour ambulatory blood pressure monitoring (ABPM) in clinical practice and observational epidemiological studies has grown considerably in the past 25 years. ABPM is a very effective tech...
Functional data often arise from measurements on fine time grids and are obtained by separating an almost continuous time record into natural consecutive intervals, for example, days. The functions th...
First of all we want to thank the editor, Michael Newton, for leading the review and discussion of our work.
Rejoinder: Likelihood Inference for Models with Unobservables Another View
Rejoinder Likelihood Inference Models Unobservables Another View
2010/10/15
First we should like to thank the editor for allowing us to respond to interesting discussions from the discussants,Molenberghs, Kenward and Verbeke (MKV), Louis and Meng, for the effort they have put...
The invitation for this discussion contribution came at the busiest time in my (professional) life with four courses and many more meetings attempting to compensate, psychologically, for the lost endo...
Implementing regularization implicitly via approximate eigenvector computation
Implementing regularization implicitly via approximate eigenvector computation
2010/10/19
Regularization is a powerful technique for extracting useful information from noisy data. Typically, it is implemented by adding some sort of norm constraint to an objective function and then exactly...
A further generalization of random self-decomposability
further generalization random self-decomposability
2010/10/19
The notion of random self-decomposability is generalized further. The notion is then extended to non-negative integer-valued distributions.
A Random Matrix--Theoretic Approach to Handling Singular Covariance Estimates
Random Matrix--Theoretic Approach Handling Singular Covariance Estimates
2010/10/19
In many practical situations we would like to estimate the covariance matrix of a set of variables from an insufficient amount of data. More specifically, if we have a set of $N$ independent, identica...
Local Optimality of User Choices and Collaborative Competitive Filtering
Local Optimality User Choices Collaborative Competitive Filtering
2010/10/14
We describe a novel framework for learning recommender models for recommendation systems, which views user-system-item interactions as an opportunity give-and-take process, and encodes both "collabora...
Asymptotic Normality of Support Vector Machines for Classification and Regression
Nonparametric regression support vector machines asymptotic normality
2010/10/14
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
Successive normalization of rectangular arrays
Normalization standardization backwards martingale convergence theorem
2010/10/14
Standard statistical techniques often require transforming data to have mean 0 and standard deviation 1. Typically, this process of "standardization" or "normalization" is applied across subjects when...
We introduce an extension of the P\'olya tree approach for constructing distributions on the space of probability measures. By using optional stopping and optional choice of splitting variables, the ...