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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Probabilistic HIV Recency Classification -- A Logistic Regression without Labeled Individual Level Training Data
概率 HIV新近度分类 个人水平训练数据 逻辑回归
2023/4/24
Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest ris...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Sequential implementation of reconstruction regression
重建回归 顺序实现 空间填充设计
2023/4/26
We propose a sequential method for implementing reconstruction regression. With a space-filling design of a small sample size, we use GP interpolation-based reconstruction regression to build initial ...
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS
ADAPTIVE SPLINE ESTIMATES NONPARAMETRIC REGRESSION MODELS
2015/8/25
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS.
Least Angle Regression
Least Angle Regression
2015/8/21
The purpose of model selection algorithms such as All Subsets, Forward Selection, and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be a...
We consider the least angle regression and forward stagewise algorithms for solving penalized least squares regression problems. In Efron,Hastie, Johnstone & Tibshirani (2004) it is proved that the le...
Genomewide Association Analysis by Lasso Penalized Logistic Regression
Genomewide Association Analysis Lasso Penalized Logistic Regression
2015/8/21
In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceed...
The Hannan-Quinn Proposition for Linear Regression
Hannan-Quinn linear regression the law of iterated logarithms strong consistency
2011/2/23
We consider the variable selection problem in linear regression. Suppose that we have a set
of random variables X1, · · · ,Xm, Y, ǫ such that Y = Pk2 αkXk +ǫ with π ⊆ {1, · · · ,m} a...
Optimal learning rates for Kernel Conjugate Gradient regression
Optimal learning rates Kernel Conjugate Gradient regression
2010/12/14
We prove rates of convergence in the statistical sense for kernel-based least squares regression using a conjugate gradient algorithm, where regularization against overfit-ting is obtained by early st...
We consider in this paper the multivariate regression problem, when the target regression matrix A is close to a low rank matrix. Our primary interest in on the practical case where the variance of th...
Pac-bayesian bounds for sparse regression estimation with exponential weights
Sparsity Oracle Inequality High-dimensional Regression
2010/12/6
We consider the sparse regression model where the number of parameters p is larger than the sample size n. The difficulty when considering high-dimensional problems is to propose estimators achieving ...
Detection boundary in sparse regression
High-dimensional regression detection boundary sparse vectors sparsity minimax hypothesis testing
2010/12/1
We study the problem of detection of a p-dimensional sparse vector of parameters in the linear regression model with Gaussian noise. We establish the detection boundary, i.e., the necessary and suffic...
Bernstein von Mises Theorems for Gaussian Regression with increasing number of regressors
Bernstein von Mises Theorems Gaussian Regression increasing number of regressors
2010/12/1
This paper brings a contribution to the Bayesian theory of nonparametric and semiparametric estimation.