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Vanilla Lasso for sparse classification under single index models
Vanilla Lasso sparse classification single index models
2016/1/20
This paper study sparse classification problems. We show that under single-index models, vanilla Lasso could give good estimate of unknown parameters. With this result, we see that even if the model i...
Independent screening for single-index hazard rate models with ultra-high dimensional features
screening univariate regression models generalized linear models single-index
2011/6/17
In data sets with many more features than observations, independent screening based on all
univariate regression models leads to a computationally convenient variable selection method.
Recent effort...
The linearity condition and adaptive estimation in single-index regressions
linearity condition adaptive estimation single-index regressions
2010/3/9
We show that under a linearity condition on the distribution of the predictors,
the coefficient vector in a single-index regression can be estimated with
the same efficiency as in the case when the ...
Optimal rates and adaptation in the single-index model using aggregation
Nonparametric regression single-index aggregation adaptation minimax random design oracle inequality
2009/9/16
We want to recover the regression function in the single-index model. Using an aggregation algorithm with local polynomial estimators, we answer in particular to the second part of Question 2 from Sto...
Optimal rates and adaptation in the single-index model using aggregation
Nonparametric regression single-index aggregation adaptation minimax random design oracle inequality
2010/4/27
We want to recover the regression function in the single-index
model. Using an aggregation algorithm with local polynomial estimators,
we answer in particular to the second part of Question 2 from S...
Spline Single-Index Prediction Model
B-spline geometric mixing knots nonparametric regression root-n rate strong consistency
2010/4/27
For the past two decades, single-index model, a special case of projection pursuit regression,
has proven to be an efficient way of coping with the high dimensional problem in nonparametric
regressi...