When Locally Linear Embedding Hits Boundary
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Hau-tieng, Wu, Nan |
|---|---|
| Format: | Preprint |
| Published: |
2018
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Convergence of Hessian estimator from random samples on a manifold with boundary
by: Chen, Chih-Wei, et al.
Published: (2023)
by: Chen, Chih-Wei, et al.
Published: (2023)
An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
by: Sasai, Takeyuki, et al.
Published: (2025)
by: Sasai, Takeyuki, et al.
Published: (2025)
Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
by: Jana, Soham, et al.
Published: (2022)
by: Jana, Soham, et al.
Published: (2022)
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
by: Sasai, Takeyuki, et al.
Published: (2022)
by: Sasai, Takeyuki, et al.
Published: (2022)
Robust Penalized Estimators for High--Dimensional Generalized Linear Models
by: Valdora, Marina, et al.
Published: (2023)
by: Valdora, Marina, et al.
Published: (2023)
Optimal estimation of a factorizable density using diffusion models with ReLU neural networks
by: Fan, Jianqing, et al.
Published: (2025)
by: Fan, Jianqing, et al.
Published: (2025)
Adaptive Ridge Approach to Heteroscedastic Regression
by: Ho, Ka Long Keith, et al.
Published: (2024)
by: Ho, Ka Long Keith, et al.
Published: (2024)
Empirical Bayes Variable Selection with Lasso Statistics in the AMP Framework
by: Hidmi, Lina, et al.
Published: (2026)
by: Hidmi, Lina, et al.
Published: (2026)
Density estimation using the perceptron
by: Gerber, Patrik Róbert, et al.
Published: (2023)
by: Gerber, Patrik Róbert, et al.
Published: (2023)
A pivotal transform for the high-dimensional location-scale model
by: van de Geer, Sara, et al.
Published: (2025)
by: van de Geer, Sara, et al.
Published: (2025)
The Influence Function of Penalized Regression Estimators
by: Öllerer, Viktoria, et al.
Published: (2015)
by: Öllerer, Viktoria, et al.
Published: (2015)
The minimax optimal convergence rate of posterior density in the weighted orthogonal polynomials
by: Luo, Yiqi, et al.
Published: (2026)
by: Luo, Yiqi, et al.
Published: (2026)
D-optimal Subsampling Design for Massive Data Linear Regression
by: Glemser, Torsten, et al.
Published: (2023)
by: Glemser, Torsten, et al.
Published: (2023)
Improving variable selection properties with data integration and transfer learning
by: Rognon-Vael, Paul, et al.
Published: (2025)
by: Rognon-Vael, Paul, et al.
Published: (2025)
Location and association measures for interval-valued data based on Mallows' distance
by: Oliveira, M. Rosário, et al.
Published: (2024)
by: Oliveira, M. Rosário, et al.
Published: (2024)
On the minimax optimality of Flow Matching through the connection to kernel density estimation
by: Kunkel, Lea, et al.
Published: (2025)
by: Kunkel, Lea, et al.
Published: (2025)
Distribution estimation via Flow Matching with Lipschitz guarantees
by: Kunkel, Lea
Published: (2025)
by: Kunkel, Lea
Published: (2025)
Assessing quality of selection procedures: Lower bound of false positive rate as a function of inter-rater reliability
by: Bartoš, František, et al.
Published: (2022)
by: Bartoš, František, et al.
Published: (2022)
Collapsing Categories for Regression with Mixed Predictors
by: Song, Chaegeun, et al.
Published: (2025)
by: Song, Chaegeun, et al.
Published: (2025)
Model selection by cross-validation in an expectile linear regression
by: Bousselmi, Bilel, et al.
Published: (2026)
by: Bousselmi, Bilel, et al.
Published: (2026)
A minimum Wasserstein distance approach to Fisher's combination of independent discrete p-values
by: Contador, Gonzalo, et al.
Published: (2023)
by: Contador, Gonzalo, et al.
Published: (2023)
Least squares for cardinal paired comparisons data
by: Singh, Rahul, et al.
Published: (2024)
by: Singh, Rahul, et al.
Published: (2024)
Euclidean Distance Deflation Under High-Dimensional Heteroskedastic Noise
by: Li, Keyi, et al.
Published: (2025)
by: Li, Keyi, et al.
Published: (2025)
Selective and marginal selective inference for exceptional groups
by: Hoff, Peter, et al.
Published: (2025)
by: Hoff, Peter, et al.
Published: (2025)
Finite-Sample Valid Rank Confidence Sets for a Broad Class of Statistical and Machine Learning Models
by: Chandra, Onrina, et al.
Published: (2025)
by: Chandra, Onrina, et al.
Published: (2025)
Kernel density estimation with polyspherical data and its applications
by: García-Portugués, Eduardo, et al.
Published: (2024)
by: García-Portugués, Eduardo, et al.
Published: (2024)
The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design
by: Tran, Huy, et al.
Published: (2022)
by: Tran, Huy, et al.
Published: (2022)
A supervised deep learning method for nonparametric density estimation
by: Bos, Thijs, et al.
Published: (2023)
by: Bos, Thijs, et al.
Published: (2023)
Pathological Regularization Regimes in Classification Tasks
by: Wiesmann, Maximilian, et al.
Published: (2024)
by: Wiesmann, Maximilian, et al.
Published: (2024)
ICS for complex data with application to outlier detection for density data
by: Mondon, Camille, et al.
Published: (2025)
by: Mondon, Camille, et al.
Published: (2025)
Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data
by: Bordoloi, Rahul, et al.
Published: (2024)
by: Bordoloi, Rahul, et al.
Published: (2024)
A High Dimensional Wild Bootstrap Max-Test for Detecting the Presence of Significant Predictors
by: Hill, Jonathan B.
Published: (2026)
by: Hill, Jonathan B.
Published: (2026)
Asymptotic properties of the normalized discrete associated-kernel estimator for probability mass function
by: Esstafa, Youssef, et al.
Published: (2022)
by: Esstafa, Youssef, et al.
Published: (2022)
Equality between two general ridge estimators and equivalence of their residual sums of squares
by: Mukasa, Hirai, et al.
Published: (2024)
by: Mukasa, Hirai, et al.
Published: (2024)
Adaptive Density Estimation Using Projection Kernels and Penalized Comparison to Overfitting
by: Hoang, Van Ha, et al.
Published: (2025)
by: Hoang, Van Ha, et al.
Published: (2025)
Estimating a density near an unknown manifold: a Bayesian nonparametric approach
by: Berenfeld, Clément, et al.
Published: (2022)
by: Berenfeld, Clément, et al.
Published: (2022)
Distributed Sparse Linear Regression under Communication Constraints
by: Fonseca, Rodney, et al.
Published: (2023)
by: Fonseca, Rodney, et al.
Published: (2023)
Poisson-Process Topic Model for Integrating Knowledge from Pre-trained Language Models
by: Austern, Morgane, et al.
Published: (2025)
by: Austern, Morgane, et al.
Published: (2025)
Estimation of sparse linear regression coefficients under $L$-subexponential covariates
by: Sasai, Takeyuki
Published: (2023)
by: Sasai, Takeyuki
Published: (2023)
Mathematical Theory of Collinearity Effects on Machine Learning Variable Importance Measures
by: Bladen, Kelvyn K., et al.
Published: (2025)
by: Bladen, Kelvyn K., et al.
Published: (2025)
Similar Items
-
Convergence of Hessian estimator from random samples on a manifold with boundary
by: Chen, Chih-Wei, et al.
Published: (2023) -
An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
by: Sasai, Takeyuki, et al.
Published: (2025) -
Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
by: Jana, Soham, et al.
Published: (2022) -
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
by: Sasai, Takeyuki, et al.
Published: (2022) -
Robust Penalized Estimators for High--Dimensional Generalized Linear Models
by: Valdora, Marina, et al.
Published: (2023)