Cover Image

Majorizing Stress Formula Two

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	de Leeuw, Jan
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis Computation Machine Learning 62-08 G.3
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Global Minima by Penalized Full-dimensional Scaling
by: de Leeuw, Jan
Published: (2024)

Higher Partials of fStress
by: de Leeuw, Jan
Published: (2024)

Convergence of SMACOF
by: De Leeuw, Jan
Published: (2024)

Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection
by: Luo, Hengrui, et al.
Published: (2024)

Forward Reverse Kernel Regression for the Schrödinger bridge problem
by: Belomestny, Denis, et al.
Published: (2025)

GOLFS: Feature Selection via Combining Both Global and Local Information for High Dimensional Clustering
by: Xing, Zhaoyu, et al.
Published: (2025)

Retrospective Counterfactual Prediction by Conditioning on the Factual Outcome: A Cross-World Approach
by: Bodik, Juraj
Published: (2026)

On the computation of the cumulative distribution function of the Normal Inverse Gaussian distribution
by: Navas-Palencia, Guillermo
Published: (2025)

Exact Bayesian inference for Markov switching diffusions
by: Stumpf-Fétizon, Timothée, et al.
Published: (2025)

Support-Conditioned Flow Matching Is Kernel Smoothing
by: Smola, Daniel Matsui
Published: (2026)

Scalable Gaussian process inference via neural feature maps
by: Stephenson, Anthony
Published: (2026)

Reducing normalizing flow complexity for MCMC preconditioning
by: Nabergoj, David, et al.
Published: (2025)

A Randomized Algorithm for Preconditioner Selection
by: DiPaolo, Conner, et al.
Published: (2019)

Data-driven quasi-interpolant spline surfaces for point cloud approximation
by: Raffo, Andrea, et al.
Published: (2019)

How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents
by: Lemberger, Pirmin, et al.
Published: (2023)

Mixture of segmentation for heterogeneous functional data
by: Brault, Vincent, et al.
Published: (2023)

SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
by: Uehara, Eichi
Published: (2026)

The upper-crossing/solution (US) algorithm for root-finding with strongly stable convergence
by: Li, Xun-Jian, et al.
Published: (2022)

An Empirical Analysis of the Laplace and Neural Tangent Kernels
by: Lencevičius, Ronaldas Paulius
Published: (2022)

Probit Monotone BART
by: Fisher, Jared D.
Published: (2025)

MCMC for multi-modal distributions
by: Łatuszyński, Krzysztof, et al.
Published: (2025)

Scalable Bernoulli factories for Bayesian inference with intractable likelihoods
by: Stumpf-Fétizon, Timothée, et al.
Published: (2025)

Conditional regression for the Nonlinear Single-Variable Model
by: Wu, Yantao, et al.
Published: (2024)

Improved Generalization Bounds for Transductive Learning by Transductive Local Complexity and Its Applications
by: Yang, Yingzhen
Published: (2023)

Improved approximation and visualization of the correlation matrix
by: Graffelman, Jan, et al.
Published: (2022)

Asymptotic confidence bands for centered purely random forests
by: Neumeyer, Natalie, et al.
Published: (2025)

Causal explanations of outliers in systems with lagged time-dependencies
by: Schwarz, Philipp Alexander, et al.
Published: (2026)

Coordinate Descent for SLOPE
by: Larsson, Johan, et al.
Published: (2022)

Least squares approximations in linear statistical inverse learning problems
by: Helin, Tapio
Published: (2022)

Efficient Decision Trees for Tensor Regressions
by: Luo, Hengrui, et al.
Published: (2024)

Sparse inverse Cholesky factorization of dense kernel matrices by greedy conditional selection
by: Huan, Stephen, et al.
Published: (2023)

Estimating a Function and Its Derivatives Under a Smoothness Condition
by: Lim, Eunji
Published: (2024)

TILT: Target-induced loss tilting under covariate shift
by: Yamamoto, Kakei, et al.
Published: (2026)

Estimating Unbounded Density Ratios: Applications in Error Control under Covariate Shift
by: Xu, Shuntuo, et al.
Published: (2025)

Wasserstein Distributionally Robust Nonparametric Regression
by: Liu, Changyu, et al.
Published: (2025)

Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
by: Huang, Dongming, et al.
Published: (2025)

Functional Partial Least-Squares: Adaptive Estimation and Inference
by: Babii, Andrii, et al.
Published: (2024)

Local Quasi-Exponential Growth Models: Kernel Differential Equation Regression and Sparse Data
by: Ge, Chunlei, et al.
Published: (2025)

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences
by: Kitch, Madeline Celi, et al.
Published: (2026)

Efficient reconstruction of multidimensional random field models with heterogeneous data using stochastic neural networks
by: Xia, Mingtao, et al.
Published: (2025)