搜索结果: 1-15 共查到“理论统计学 approximation”相关记录51条 . 查询时间(0.168 秒)
Approximation of Solitons in the Discrete NLS Equation
Discrete soliton one dimensional discrete nonlinear schrodinger equation
2014/12/24
We study four different approximations for finding the profile of discrete solitons in the one- dimensional Discrete Nonlinear Schrödinger (DNLS) Equation. Three of them are discrete approximatio...
Approximation of epidemic models by diffusion processes and their statistical inference
Approximation epidemic models diffusion processes their statistical inference
2013/6/14
Among various mathematical frameworks, multidimensional continuous-time Markov jump processes $(Z_t)$ on $\N^d$ form a natural set-up for modeling $SIR$-like epidemics. In this study we extend the res...
On Approximation of the Backward Stochastic Differential Equation
Backward SDE approximation of the solution small noise asymptotics
2013/6/14
We consider the problem of approximation of the solution of the backward stochastic differential equation in the Markovian case. We suppose that the trend coefficient of the diffusion process depends ...
Efficient Density Estimation via Piecewise Polynomial Approximation
Efficient Density Estimation Piecewise Polynomial Approximation
2013/6/14
We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary dis...
A least-squares method for sparse low rank approximation of multivariate functions
least-squares method sparse low rank approximation multivariate functions
2013/6/14
In this paper, we propose a low-rank approximation method based on discrete least-squares for the approximation of a multivariate function from random, noisy-free observations. Sparsity inducing regul...
Universal Approximation Depth and Errors of Narrow Belief Networks with Discrete Units
Deep belief network restricted Boltzmann machine universal approxima-tion representational power Kullback-Leibler divergence,q-ary variable
2013/4/28
We generalize recent theoretical work on the minimal number of layers of narrow deep belief networks that can approximate any probability distribution on the states of their visible units arbitrarily ...
Sparse approximation and recovery by greedy algorithms in Banach spaces
Sparse approximation recovery greedy algorithms Banach spaces
2013/4/28
We study sparse approximation by greedy algorithms. We prove the Lebesgue-type inequalities for the Weak Chebyshev Greedy Algorithm (WCGA), a generalization of the Weak Orthogonal Matching Pursuit to ...
Approximation for the Distribution of Three-dimensional Discrete Scan Statistic
Approximation for the Distribution Three-dimensional Discrete Scan Statistic
2013/4/27
We consider the discrete three dimensional scan statistics. Viewed as the maximum of an 1-dependent stationary r.v.'s sequence, we provide approximations and error bounds for the probability distribut...
A Greedy Approximation of Bayesian Reinforcement Learning with Probably Optimistic Transition Model
Reinforcement Learning Uncertain Knowledge Probabilistic Reasoning Optimal Behavior in Polynomial Time
2013/5/2
Bayesian Reinforcement Learning (RL) is capable of not only incorporating domain knowledge, but also solving the exploration-exploitation dilemma in a natural way. As Bayesian RL is intractable except...
Smoothing effect of Compound Poisson approximation to distribution of weighted sums
characteristic function concentration function compound Poisson distribution Kolmogorov norm weighted random variables.
2013/4/27
The accuracy of compound Poisson approximation to the sum $S=w_1S_1+w_2S_2+...+w_NS_N$ is estimated.
Here $S_i$ are sums of independent or weakly dependent random variables, and $w_i$ denote weights...
Approximation properties of certain operator-induced norms on Hilbert spaces
L2 approximation Empirical norm Quadratic functionals Hilbert spaces with reproducing kernels Analysis of M-estimators
2011/6/20
We consider a class of operator-induced norms, acting as finite-dimensional
surrogates to the L2 norm, and study their approximation properties over
Hilbert subspaces of L2. The class includes, as a...
Almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case
Kesten's stochastic approximation algorithm multidimensional
2011/6/20
It is shown the almost sure convergence and asymptotical normality of a generalization of
Kesten's stochastic approximation algorithm for multidimensional case.
In this generalization, the step incr...
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Submodular meets Spectral Greedy Algorithms for Subset Selection Sparse Approximation Dictionary Selection
2011/3/23
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
Selecting the rank of SVD by Maximum Approximation Capacity
Approximation Capacity Selecting the rank of SVD
2011/3/25
Truncated Singular Value Decomposition (SVD) calculates the closest rank-k approximation of a given input matrix. Selecting the appropriate rank k defines a critical model order choice in most applica...
Uncertainty quantification and weak approximation of an elliptic inverse problem
Uncertainty quantification weak approximation elliptic inverse problem
2011/3/18
We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a lin...