Image de couverture de livre

Scale-Calibrated Median-of-Means for Robust Distributed Principal Component Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	You, Kisung
Format:	Preprint
Publié:	2026
Sujets:	Methodology Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Quotient-Based Posterior Analysis for Euclidean Latent Space Models
par: You, Kisung, et autres
Publié: (2026)

Learning over von Mises-Fisher Distributions via a Wasserstein-like Geometry
par: You, Kisung, et autres
Publié: (2025)

PCA, SVD, and Centering of Data
par: Kim, Donggun, et autres
Publié: (2023)

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
par: You, Kisung
Publié: (2026)

Casewise and Cellwise Robust Multilinear Principal Component Analysis
par: Hirari, Mehdi, et autres
Publié: (2025)

Dirichlet Process-based Robust Clustering using the Median-of-Means Estimator
par: Basu, Supratik, et autres
Publié: (2023)

Sequential Gibbs Posteriors with Applications to Principal Component Analysis
par: Winter, Steven, et autres
Publié: (2023)

On the Wasserstein Geodesic Principal Component Analysis of probability measures
par: Vesseron, Nina, et autres
Publié: (2025)

Convex Clustering Redefined: Robust Learning with the Median of Means Estimator
par: De, Sourav, et autres
Publié: (2025)

Online Functional Principal Component Analysis on a Multidimensional Domain
par: Nanshan, Muye, et autres
Publié: (2025)

Principal Component Analysis When n < p: Challenges and Solutions
par: Weeraratne, Nuwan, et autres
Publié: (2025)

Hierarchical Probabilistic Principal Component Analysis of Longitudinal Data
par: Zhang, Xinyu, et autres
Publié: (2026)

Median of Means Sampling for the Keister Function
par: Zhang, Bocheng
Publié: (2025)

Robust Variational Bayes by Min-Max Median Aggregation
par: Yan, Jiawei, et autres
Publié: (2025)

Finite Mixture Modeling with Riemannian Gaussian Distributions on Hyperbolic Space
par: You, Kisung
Publié: (2026)

Distributional Principal Autoencoders
par: Shen, Xinwei, et autres
Publié: (2024)

Nonlinear Principal Component Analysis with Random Bernoulli Features for Process Monitoring
par: Chen, Ke, et autres
Publié: (2025)

Scale selection for geometric medians on product manifolds
par: You, Kisung
Publié: (2026)

Adaptive Principal Component Regression with Applications to Panel Data
par: Agarwal, Anish, et autres
Publié: (2023)

Soft Mean Expected Calibration Error (SMECE): A Calibration Metric for Probabilistic Labels
par: Leznik, Michael
Publié: (2026)

Localized Sparse Principal Component Analysis of Multivariate Time Series in Frequency Domain
par: Namdari, Jamshid, et autres
Publié: (2024)

On Heterogeneity in Wasserstein Space
par: You, Kisung
Publié: (2026)

Constant Metric Scaling in Riemannian Computation
par: You, Kisung
Publié: (2026)

MCMC with Adaptive Principal-Component Transformation: Rotation-Invariant Universal Samplers for Bayesian Structural System Identification
par: Meng, Xianghao, et autres
Publié: (2026)

Joint Linked Component Analysis for Multiview Data
par: Xiao, Lin, et autres
Publié: (2024)

Conformalized Robust Principal Component Analysis
par: Yuan, Liangliang, et autres
Publié: (2026)

Gradient Boosted Mixed Models: Flexible Joint Estimation of Mean and Variance Components for Clustered Data
par: Prevett, Mitchell L., et autres
Publié: (2025)

Multi-Distribution Robust Conformal Prediction
par: Yang, Yuqi, et autres
Publié: (2026)

Flow-based Distributionally Robust Optimization
par: Xu, Chen, et autres
Publié: (2023)

Additive Distributionally Robust Ranking and Selection
par: Li, Zaile, et autres
Publié: (2025)

Knowledge-Guided Wasserstein Distributionally Robust Optimization
par: Wang, Zitao, et autres
Publié: (2025)

Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
par: Li, Yufan, et autres
Publié: (2025)

Conditional Distribution Compression via the Kernel Conditional Mean Embedding
par: Broadbent, Dominic, et autres
Publié: (2025)

Distribution-Free Robust Predict-Then-Optimize in Function Spaces
par: Patel, Yash, et autres
Publié: (2026)

Robust Bayesian Functional Principal Component Analysis
par: Zhang, Jiarui, et autres
Publié: (2023)

Spectrum-Aware Debiasing: A Modern Inference Framework with Applications to Principal Components Regression
par: Li, Yufan, et autres
Publié: (2023)

Robust Validation: Confident Predictions Even When Distributions Shift
par: Cauchois, Maxime, et autres
Publié: (2020)

Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
par: Wang, Zhenyu, et autres
Publié: (2023)

Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains
par: Wilkins-Reeves, Steven, et autres
Publié: (2024)

Geometric medians on product manifolds
par: Park, Jiewon, et autres
Publié: (2025)