Nonlinear multi-output regression on unknown input manifold
DOI10.1007/s10472-017-9551-0zbMath1386.68133OpenAlexW2616071654MaRDI QIDQ1680851
Publication date: 16 November 2017
Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10472-017-9551-0
dimensionality reductionmanifold learningmanifold estimationregression on feature spaceregression on manifolds
Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)
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- Greedy function approximation: A gradient boosting machine.
- Intrinsic dimension estimation of manifolds by incising balls
- Optimal rates of convergence for nonparametric estimators
- Introductory lectures on convex optimization. A basic course.
- Intrinsic dimension estimation: relevant techniques and a benchmark framework
- Optimal global rates of convergence for nonparametric regression
- Principal component analysis.
- A general theory for nonlinear sufficient dimension reduction: formulation and estimation
- Geodesic regression and the theory of least squares on Riemannian manifolds
- Multi-output regression on the output manifold
- Regression on manifolds: estimation of the exterior derivative
- Manifold reconstruction using tangential Delaunay complexes
- Finding the homology of submanifolds with high confidence from random samples
- An improved incremental nonlinear dimensionality reduction for isometric data embedding
- Incremental locally linear embedding
- Vector diffusion maps and the connection Laplacian
- Reducing the Dimensionality of Data with Neural Networks
- 10.1162/153244304322972667
- Deep Learning: Methods and Applications
- A kernel-based classifier on a Riemannian manifold
- Sufficient dimension reduction and prediction in regression
- Local Regression and Likelihood
- Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
- 10.1162/1532443041827934
- An Introduction to Statistical Learning
- Tangent space estimation for smooth embeddings of Riemannian manifolds
- Non-asymptotic analysis of tangent space perturbation
- Fibonacci heaps and their uses in improved network optimization algorithms
- On power and sample size determinations for the Wilcoxon–Mann–Whitney test
- Characterizations of Life Distributions Using Conditional Expectations of Doubly (Interval) Truncated Random Variables
- Local Linear Regression on Manifolds and Its Geometric Interpretation
- All of Nonparametric Statistics
- Nonparametric Regression between General Riemannian Manifolds
- Riemannian geometry and geometric analysis
- Random forests
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