搜索结果: 1-15 共查到“理学 minimax”相关记录33条 . 查询时间(0.062 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Primal Dual Alternating Proximal Gradient Algorithms for Nonsmooth Nonconvex Minimax Problems with Coupled Linear Constraints
耦合 线性约束 非光滑 非凸极小问题 基本对偶交替 近端梯度算法
2023/4/14
Nonconvex minimax problems have attracted wide attention in machine learning, signal processing and many other fields in recent years. In this paper, we propose a primal dual alternating proximal grad...
Minimax Risk: Pinsker Bound
COMMUNICATION THEORY, STATISTICAL DENSITY ESTIMATION FISHER INFORMATION KERNEL ESTIMATORS LINEAR ESTIMATORS, BAYES LOCAL ASYMPTOTIC NORMALITY METHOD OF SIEVES MINIMAX ESTIMATION NOISE (SIGNAL PROCESSING IN THE PRESENCE OF ) PREDICTION AND FILTERING LINEAR SIEVES, METHOD OF SPECTRAL ANALYSIS SHRINKAGE ESTIMATORS SMOOTHNESS PRIORS SOBOLEV SPACES SPLINE FUNCTIONS STATIONARY PROCESSES STEIN EFFECT
2015/8/25
We give an account of the Pinsker bound describing the exact asymptotics of the minimax risk in a class of nonparametric smoothing problems. The parameter spaces are Sobolev classes or ellipsoids, and...
The Asymptotic Minimax Constant for Sup-Norm Loss in Nonparametric Density Estimation
Density estimation exact constant optimal recovery uniform norm risk white noise
2015/8/25
We develop the exact constant of the risk asymptotics in the uniform norm for density estimation. This constant has first been found for nonparametric regression and for signal estimation in Gaussian ...
Consider estimating the mean vector from data Nn(; 2I ) with lq norm loss,
q 1, when is known to lie in an n-dimensional lp ball, p 2 (0; 1). For large
n, the ratio of minimax linear risk to...
On minimax estimation of a sparse normal mean vector
nearly black object robustness white noise model
2015/8/20
Mallows has conjectured that among distributions which are Gaussian but
for occasional contamination by additive noise, the one having least Fisher
information has (two-sided) geometric contaminatio...
Minimax Bayes, asymptotic minimax and sparse wavelet priors
Minimax Decision theory Minimax Bayes estimation
2015/8/20
Pinsker(1980) gave a precise asymptotic evaluation of the minimax mean squared
error of estimation of a signal in Gaussian noise when the signal is known a priori
to lie in a compact ellipsoid in Hi...
We attempt to recover an unknown function from noisy, sampled data. Using
orthonormal bases of compactly supported wavelets we develop a nonlinear method
which works in the wavelet domain by simple ...
Neo-Classical Minimax Problems, Thresholding, and Adaptation
Minimax Estimation Adaptive Estimation
2015/8/20
We study the problem of estimating from data Y N(; 2
) under squared-error loss.
We de ne three new scalar minimax problems in which the risk is weighted by the size of .
Simple thresholding...
A minimax theorem with applications to machine learning, signal processing, and finance
convex optimization minimax theorem robust optimization
2015/8/10
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)...
Minimax adaptive tests for the Functional Linear model
Functional linear regression eigenfunction principal com-ponent analysis adaptive testing minimax hypothesis testing
2012/6/21
We introduce two novel procedures to test the nullity of the slope function in the functional linear model with real output. The test statistics combine multiple testing ideas and random projections o...
Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence
nonparametric regression long-range dependence kink minimax
2011/9/22
Abstract: In this paper, a lower bound is determined in the minimax sense for change point estimators of the first derivative of a regression function in the fractional white noise model. Similar mini...
Minimax-Optimal Bounds for Detectors Based on Estimated Prior Probabilities
Minimax-optimal bounds detector prior probability maximum likelihood estimate statistical learning theory
2011/9/29
Abstract: In many signal detection and classification problems, we have knowledge of the distribution under each hypothesis, but not the prior probabilities. This paper is aimed at providing theory to...
Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality
density estimation kernel estimators Lp–risk oracle inequalities adaptive estimation
2010/11/30
We address the problem of density estimation with L p–loss by selection of kernel estimators. We develop a selection procedure and derive corresponiding L p–risk oracle inequalities. It is shown that ...
Minimax estimation of the scale parameter of the selected gamma population with arbitrary known shape parameter
Exponential Family Family of transformed chi-square distributions
2010/9/17
Let X1, X2 be independent random variables from gamma populations Π1,Π2 with common arbitrary known shape parameter α and unknown scale parameters θ1, θ2 respectively. Suppose X(1), X(2) be the order ...
求解Minimax优化问题的Newton型算法
Newton型算法 Minimax优化
2009/10/23
In this paper, a Newton like method for solving minimax optimization problems was proposed. The method belong to sequential quadratic programming method, the Hessian of quadratic programming subproble...