Metric Learning via Cross-Validation
From MaRDI portal
Publication:5089466
DOI10.5705/ss.202020.0398OpenAlexW3175497080MaRDI QIDQ5089466
Gang Li, Linlin Dai, Kani Chen, Yuanyuan Lin
Publication date: 19 July 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202020.0398
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A constructive approach to the estimation of dimension reduction directions
- Sliced Regression for Dimension Reduction
- Projection pursuit multi-index (PPMI) models
- Single and multiple index functional regression models with nonparametric link
- On projection pursuit regression
- A sparse eigen-decomposition estimation in semiparametric regression
- Contour projected dimension reduction
- Structure adaptive approach for dimension reduction.
- Dimension reduction for conditional mean in regression
- Support-vector networks
- Dimensionality determination: a thresholding double ridge ratio approach
- Optimal smoothing in single-index models
- On kernel method for sliced average variance estimation
- Determining the dimension of iterative Hessian transformation
- Dimension reduction via marginal high moments in regression
- Estimating the Structural Dimension of Regressions Via Parametric Inverse Regression
- Consistently determining the number of factors in multivariate volatility modelling
- Exploring Regression Structure Using Nonparametric Functional Estimation
- Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
- Investigating Smooth Multiple Regression by the Method of Average Derivatives
- Principal Hessian Directions Revisited
- Sliced Inverse Regression for Dimension Reduction
- On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
- Generalized Partially Linear Single-Index Models
- Extending Sliced Inverse Regression
- Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
- An Adaptive Estimation of Dimension Reduction Space
- A Semiparametric Approach to Dimension Reduction
- An oracle property of the Nadaraya–Watson kernel estimator for high‐dimensional nonparametric regression
- Random-projection Ensemble Classification
- Combining eigenvalues and variation of eigenvectors for order determination
- Sparse single-index model
- A Multiple-Index Model and Dimension Reduction
- Marginal tests with sliced average variance estimation
- Nearest neighbor pattern classification
- On Estimation Efficiency of the Central Mean Subspace
- Sufficient Dimension Reduction via Inverse Regression
- On Sliced Inverse Regression With High-Dimensional Covariates