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A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
Inferring Label Sampling Mechanisms Semi-Supervised Learning
2015/8/21
We consider the situation in semi-supervised learning, where the “label sampling” mechanism stochastically depends on the true response (as well as potentially on the features). We suggest a method of...
We propose a sketch-based sampling algorithm, which effectively exploits the data sparsity. Sampling methods have become popular in large-scale data mining and information retrieval, where high data s...
Margin-constrained Random Projections And Very Sparse Random Projections
Random Projections Sampling Maximum Likelihood Asymptotic Analysis
2015/8/21
We propose methods for improving both the accuracy and efficiency of random projections, the popular dimension reduction technique in machine learning and data mining, particularly useful for estimati...
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A ∈ Rn×D be our n points i...
One Sketch For All:Theory and Application of Conditional Random Sampling
One Sketch For All Theory and Application Conditional Random Sampling
2015/8/21
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the original CRS and exten...
Estimation of a probability in inverse binomial sampling under normalized linear-linear and inverse-linear loss
Sequential estimation Point estimator Inverse binomial sampling
2010/12/3
Sequential estimation of the success probability p in inverse binomial sam-pling is considered in this paper. For any estimator ˆp, its quality is measured by the risk associated with normalized ...
Path sampling for particle filters with application to multi-target tracking
Path sampling particle filters with application multi-target tracking
2010/12/3
In recent work [15], we have presented a novel approach for improving particle filters for multi-target tracking. The suggested approach was based on Girsanov’s change of measure theorem for stochasti...
Sampling and Recovery of Multidimensional Bandlimited Functions via Frames
Sampling and Recovery Multidimensional Bandlimited Functions
2010/12/3
In this paper, we investigate frames for L2[−, ]d consisting of exponential functions in connection to oversampling and nonuniform sampling of bandlimited func-tions.
分析了性能指标环境因子与寿命环境因子在概念和应用中的差异.给出了性能指标环境因子的一般性定义,并导出了正态分布环境因子的表达式. 利用这一结果,可以在一定条件下将不同环境的试验数据相互折合, 从而增加样本量,有利于进一步的统计推断. 最后通过实例,说明了性能指标环境因子的应用方法和步骤.
二阶抽样总体比率的估计
二阶抽样 总体比率 PPS抽样 比估计量
2008/11/25
本文研究二阶抽样下总体比率的估计问题, 就若干种情形给出总体比率的几种可行的估计量,
讨论了它们的统计性质.