搜索结果: 1-13 共查到“管理学 dimensionality”相关记录13条 . 查询时间(0.134 秒)
How to Deal with the Curse of Dimensionality of Likelihood Ratios in Monte Carlo Simulation
Cross-entropy Rare-event probability estimation Screening Simulation
2015/7/6
In this work we show how to resolve, at least partially, the curse of dimensionality of likelihood ratios (LRs) while using importance sampling (IS) to estimate the performance of high-dimensional Mon...
Dark matter-wave solitons in the dimensionality crossover
Soliton statics dynamics and dimension crossover regime schrodinger mean-field model
2014/12/25
We consider the statics and dynamics of dark matter-wave solitons in the dimensionality crossover regime from three dimensions (3D) to one dimension (1D). There, using the nonpolynomial Schröding...
Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
Non-linear dimensionality reduction Riemannian metric estimation the problem geometric discovery
2013/6/14
In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degre...
Inverting Non-Linear Dimensionality Reduction with Scale-Free Radial Basis Interpolation
nonlinear dimensionality reduction graph Laplacian radial basis function interpolation Nyströ m method
2013/6/14
A numerical method is proposed to approximate the inverse of a general bi-Lipschitz nonlinear dimensionality reduction mapping, where the forward and consequently the inverse mappings are only explici...
EXPLORING THE DIMENSIONALITY OF SERVICE QUALITY: AN APPLICATION OF TOPSIS IN THE INDIAN BANKING INDUSTRY
banking dimensionality performance evaluation Service quality
2011/11/1
The Indian banking industry is going through turbulent times. With the lowering of entry barriers and blurring product lines of banks and non-banks since the financial sector reforms, banks are functi...
Tight conditions for consistency of variable selection in the context of high dimensionality
variable selection nonparametric regression set estimation sparsity pattern
2011/7/6
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of variables is very large. The main focus is on the situation where the numb...
A convex model for non-negative matrix factorization and dimensionality reduction on physical space
Non-negative matrix factorization dictionary learning subset selection dimensionality reduction hyperspec-tral endmember detection blind source separation
2011/3/18
A collaborative convex framework for factoring a data matrix $X$ into a non-negative product $AS$, with a sparse coefficient matrix $S$, is proposed. We restrict the columns of the dictionary matrix $...
A multivariate adaptive stochastic search method for dimensionality reduction in classification
Dimensionality reduction classification variable selection
2010/10/19
High-dimensional classification has become an increasingly important problem. In this paper we propose a "Multivariate Adaptive Stochastic Search" (MASS) approach which first reduces the dimension of...
Sure Independence Screening in Generalized Linear Models with NP-Dimensionality
generalized linear models independent learning sure indepen-dent screening variable selection
2010/3/19
Ultrahigh dimensional variable selection plays an increasingly
important role in contemporary scientific discoveries and statisti-
cal research. Among others, Fan and Lv (2008) propose an indepen-
...
CURSE OF DIMENSIONALITY IN APPROXIMATION OF RANDOM FIELDS
Random fields Gaussian processes fractional Brownian sheet linear approximation error
2009/9/18
Consider a random field of tensor product-type X (t),
~ E [ O l, l d, given by
where ( A ( ~ ) i , 0 ~ 1 2 , is an orthonormal system in L, KO, 11 and
(tklkENd are non-correlated random variables w...
A scale-based approach to finding effective dimensionality in manifold learning
Primary manifold learning intrinsic dimension scale space secondary hypothesis test multivariate analysis
2009/9/16
The discovering of low-dimensional manifolds in high-dimensional data is one of the main goals in manifold learning. We propose a new approach to identify the effective dimension (intrinsic dimension)...
NEW CRITERIA FOR TESTS OF DIMENSIONALITY UNDER ELLIPTICAL POPULATIONS
Elliptical distribution dimensionality multivariate analysis of variance nuisance parameter
2009/3/11
We consider tests of dimensionality in the multivariate analysis of variance (MANOVA). Three types of test criteria (Likelihood-Ratio-type, Lawley-Hotelling-type and Bartlett-Nanda-Pillai-type) are po...
Escaping the curse of dimensionality with a tree-based regressor
curse dimensionality tree-based regressor
2010/3/18
We present the first tree-based regressorwhose convergence
rate depends only on the intrinsic dimension
of the data, namely its Assouad dimension.
The regressor uses the RPtree partitioning procedu...