Cover Image

High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Léger, Victor, Chatelain, Florent
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spectral Thresholds in Correlated Spiked Models and Fundamental Limits of Partial Least Squares
by: Mergny, Pierre, et al.
Published: (2025)

Asymptotic Gaussian Fluctuations of Eigenvectors in Spectral Clustering
by: Lebeau, Hugo, et al.
Published: (2024)

A Large Dimensional Analysis of Multi-task Semi-Supervised Learning
by: Leger, Victor, et al.
Published: (2024)

$(ε, δ)$-Differentially Private Partial Least Squares Regression
by: Nikzad-Langerodi, Ramin, et al.
Published: (2024)

The Fundamental Limits of Least-Privilege Learning
by: Stadler, Theresa, et al.
Published: (2024)

High-Dimensional Privacy-Utility Dynamics of Noisy Stochastic Gradient Descent on Least Squares
by: Lin, Shurong, et al.
Published: (2025)

Partitioned Least Squares
by: Esposito, Roberto, et al.
Published: (2020)

A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
by: Lebeau, Hugo, et al.
Published: (2024)

P3LS: Partial Least Squares under Privacy Preservation
by: Duy, Du Nguyen, et al.
Published: (2024)

DAPLSR: Data Augmentation Partial Least Squares Regression Model via Manifold Optimization
by: Chen, Haoran, et al.
Published: (2025)

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

PLeaS -- Merging Models with Permutations and Least Squares
by: Nasery, Anshul, et al.
Published: (2024)

Outlier-robust Autocovariance Least Square Estimation via Iteratively Reweighted Least Square
by: Li, Jiahong, et al.
Published: (2026)

Towards Learning High-Precision Least Squares Algorithms with Sequence Models
by: Liu, Jerry, et al.
Published: (2025)

Optimal Spectral Transitions in High-Dimensional Multi-Index Models
by: Defilippis, Leonardo, et al.
Published: (2025)

Communication-Efficient l_0 Penalized Least Square
by: Gong, Chenqi, et al.
Published: (2025)

On Least Square Estimation in Softmax Gating Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)

Ordinary Least Squares as an Attention Mechanism
by: Coulombe, Philippe Goulet
Published: (2025)

Core-elements Subsampling for Alternating Least Squares
by: Xue, Dunyao, et al.
Published: (2025)

Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems
by: Su, Junwei, et al.
Published: (2024)

A Hybrid Federated Kernel Regularized Least Squares Algorithm
by: Damiani, Celeste, et al.
Published: (2024)

Asymptotic Bayes risk of semi-supervised learning with uncertain labeling
by: Leger, Victor, et al.
Published: (2024)

Transformers Don't In-Context Learn Least Squares Regression
by: Hill, Joshua, et al.
Published: (2025)

Kernel Recursive Least Squares Dictionary Learning Algorithm
by: Alipoor, Ghasem, et al.
Published: (2025)

Generalization for Least Squares Regression With Simple Spiked Covariances
by: Li, Jiping, et al.
Published: (2024)

Convex Regression in Multidimensions: Suboptimality of Least Squares Estimators
by: Kur, Gil, et al.
Published: (2020)

Randomized Least Squares Value Iteration itself is Joint Differentially Private
by: Lu, Haiyang, et al.
Published: (2026)

Generalized Least Squares Kernelized Tensor Factorization
by: Lei, Mengying, et al.
Published: (2024)

Intelligent Materials Modelling: Large Language Models Versus Partial Least Squares Regression for Predicting Polysulfone Membrane Mechanical Performance
by: Cao, Dingding, et al.
Published: (2026)

Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
by: Shen, Dennis, et al.
Published: (2023)

Shape Constraints in Symbolic Regression using Penalized Least Squares
by: Martinek, Viktor, et al.
Published: (2024)

Importance Weighting Correction of Regularized Least-Squares for Target Shift
by: Gogolashvili, Davit
Published: (2022)

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares
by: Brown, Gavin, et al.
Published: (2024)

A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization
by: Kim, Hideaki, et al.
Published: (2025)

Tensor-Based Foundations of Ordinary Least Squares and Neural Network Regression Models
by: Algarte, Roberto Dias
Published: (2024)

Enhancing Robustness and Efficiency of Least Square Twin SVM via Granular Computing
by: Tanveer, M., et al.
Published: (2024)

Online Multi-Task Learning with Recursive Least Squares and Recursive Kernel Methods
by: Lencione, Gabriel R., et al.
Published: (2023)

Least Squares Training of Quadratic Convolutional Neural Networks with Applications to System Theory
by: Van Egmond, Zachary Yetman, et al.
Published: (2024)

Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent
by: Schertzer, Adrien, et al.
Published: (2024)

Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications
by: Xu, Yizhou, et al.
Published: (2025)