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Sufficient dimension reduction

In statistics, sufficient dimension reduction (SDR) is a paradigm for analyzing data that combines the ideas of dimension reduction with the concept… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

1999-2018
051019992018

Related topics

Related topics

9 relations
Basis (linear algebra)Convex setCurse of dimensionalityDimensionality reduction
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Related mentions per year

Related mentions per year

1937-2018
19401960198020002020
Sufficient dimension reduction
Principal component analysis
Dimensionality reduction
Linear discriminant analysis
Convex set
Ordinary least squares

Papers overview

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2015
2015
Sufficient Dimension Reduction for Longitudinal Data
Correlation structure contains important information about longitudinal data. Existing sufficient dimension reduction approaches… (More)
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2013
2013
Sparse sufficient dimension reduction using optimal scoring
Sufficient dimension reduction is a body of theory and methods for reducing the dimensionality of predictors while preserving… (More)
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2010
2010
Sufficient dimension reduction for visual sequence classification
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training… (More)
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Highly Cited
2010
Highly Cited
2010
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
The goal of sufficient dimension reduction in supervised learning is to find the low-dimensional subspace of input features that… (More)
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2008
2008
Likelihood-based Sufficient Dimension Reduction
We obtain the maximum likelihood estimator of the central subspace under conditional normality of the predictors given the… (More)
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2008
2008
Sufficient Dimension Reduction Summaries
Observational studies assessing causal or non-causal relationships between an explanatory measure and an outcome can be… (More)
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2008
2008
Sufficient Dimension Reduction With Missing Predictors
In high-dimensional data analysis, sufficient dimension reduction (SDR) methods are effective in reducing the predictor dimension… (More)
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Highly Cited
2005
Highly Cited
2005
Sufficient Dimension Reduction via Inverse Regression: A Minimum Discrepancy Approach
A family of dimension-reduction methods, the inverse regression (IR) family, is developed by minimizing a quadratic objective… (More)
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2005
2005
Sufficient dimension reduction in regressions across heterogeneous subpopulations
Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromonte and co-workers extended this method… (More)
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2004
2004
Testing Predictor Contributions in Sufficient Dimension Reduction
We develop tests of the hypothesis of no effect for selected predictors in regression, without assuming a model for the… (More)
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