scientific article; zbMATH DE number 7255041

zbMath1475.68263MaRDI QIDQ4969042

Zhanrui Cai, Run-Ze Li, Li-ping Zhu

Publication date: 5 October 2020

Full work available at URL: https://jmlr.csail.mit.edu/papers/v21/18-567.html

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

perturbationsingular value decompositiondimension reductiononline learninggradient descentsliced inverse regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Learning and adaptive systems in artificial intelligence (68T05) Online algorithms; streaming algorithms (68W27)

Related Items (5)

Online sparse sliced inverse regression for high-dimensional streaming data ⋮ On expectile-assisted inverse regression estimation for sufficient dimension reduction ⋮ Network Functional Varying Coefficient Model ⋮ Advanced topics in sliced inverse regression ⋮ Computational Outlier Detection Methods in Sliced Inverse Regression

Uses Software

• e1071

Cites Work

• On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
• Stochastic approximation methods for constrained and unconstrained systems
• A sliced inverse regression approach for data stream
• Online Learning as Stochastic Approximation of Regularization Paths: Optimality and Almost-Sure Convergence
• On Directional Regression for Dimension Reduction
• Sliced Inverse Regression for Dimension Reduction
• 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
• A Review on Dimension Reduction
• Dimension Reduction in Regressions Through Cumulative Slicing Estimation
• On the asymptotic behaviour of the recursive Nadaraya–Watson estimator associated with the recursive sliced inverse regression method
• Quasi-Martingales
• Online Principal Components Analysis
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