Imagen de Portada

Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tao, Qinghua, Tonin, Francesco, Lambert, Alex, Chen, Yingyi, Patrinos, Panagiotis, Suykens, Johan A. K.
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
por: Chen, Yingyi, et al.
Publicado: (2024)

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification
por: Achten, Sonny, et al.
Publicado: (2023)

Accelerating Spectral Clustering under Fairness Constraints
por: Tonin, Francesco, et al.
Publicado: (2025)

Rethinking PCA Through Duality
por: Quan, Jan, et al.
Publicado: (2025)

HeNCler: Node Clustering in Heterophilous Graphs via Learned Asymmetric Similarity
por: Achten, Sonny, et al.
Publicado: (2024)

Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
por: He, Fan, et al.
Publicado: (2024)

Learning to Drive Safely with Hybrid Options
por: De Cooman, Bram, et al.
Publicado: (2025)

A Dual Perspective of Reinforcement Learning for Imposing Policy Constraints
por: De Cooman, Bram, et al.
Publicado: (2024)

Sparsity via Sparse Group $k$-max Regularization
por: Tao, Qinghua, et al.
Publicado: (2024)

Generative Kernel Spectral Clustering
por: Winant, David, et al.
Publicado: (2025)

Nyström Kernel Stein Discrepancy
por: Kalinke, Florian, et al.
Publicado: (2024)

Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
por: Ozaslan, Ibrahim K., et al.
Publicado: (2024)

Newton methods beyond Hessian Lipschitz continuity: A nonlinear preconditioning approach
por: Bodard, Alexander, et al.
Publicado: (2026)

Nyström Kernel Stein Discrepancy Tests
por: Kalinke, Florian, et al.
Publicado: (2026)

MaD-Mix: Multi-Modal Data Mixtures via Latent Space Coupling for Vision-Language Model Training
por: Xie, Wanyun, et al.
Publicado: (2026)

Efficient Large Language Model Inference with Neural Block Linearization
por: Erdogan, Mete, et al.
Publicado: (2025)

On the Nystrom Approximation for Preconditioning in Kernel Machines
por: Abedsoltan, Amirhesam, et al.
Publicado: (2023)

SVD-NO: Learning PDE Solution Operators with SVD Integral Kernels
por: Koren, Noam, et al.
Publicado: (2025)

On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
por: Latafat, Puya, et al.
Publicado: (2023)

Block-coordinate and incremental aggregated proximal gradient methods for nonsmooth nonconvex problems
por: Latafat, Puya, et al.
Publicado: (2019)

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization
por: Bodard, Alexander, et al.
Publicado: (2025)

ERC-SVD: Error-Controlled SVD for Large Language Model Compression
por: Bai, Haolei, et al.
Publicado: (2025)

DipSVD: Dual-importance Protected SVD for Efficient LLM Compression
por: Ding, Xuan, et al.
Publicado: (2025)

SVDformer: Direction-Aware Spectral Graph Embedding Learning via SVD and Transformer
por: Fang, Jiayu, et al.
Publicado: (2025)

Bi-Level Policy Optimization with Nyström Hypergradients
por: Prakash, Arjun, et al.
Publicado: (2025)

Post-processing for Fair Regression via Explainable SVD
por: Zuo, Zhiqun, et al.
Publicado: (2025)

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models
por: Hong, Chengjie, et al.
Publicado: (2026)

Escaping saddle points without Lipschitz smoothness: the power of nonlinear preconditioning
por: Bodard, Alexander, et al.
Publicado: (2025)

Anisotropic Proximal Point Algorithm
por: Laude, Emanuel, et al.
Publicado: (2023)

Cyqlone: A Parallel, High-Performance Linear Solver for Optimal Control
por: Pas, Pieter, et al.
Publicado: (2025)

Blocked Cholesky factorization updates of the Riccati recursion using hyperbolic Householder transformations
por: Pas, Pieter, et al.
Publicado: (2025)

Anisotropic Proximal Gradient
por: Laude, Emanuel, et al.
Publicado: (2022)

Enhancing Delta Compression in LLMs via SVD-based Quantization Error Minimization
por: Xiong, Boya, et al.
Publicado: (2025)

Parametric Nonconvex Optimization via Convex Surrogates
por: Wang, Renzi, et al.
Publicado: (2026)

Learning Reconstructive Embeddings in Reproducing Kernel Hilbert Spaces via the Representer Theorem
por: Feito-Casares, Enrique, et al.
Publicado: (2026)

SPGCL: Simple yet Powerful Graph Contrastive Learning via SVD-Guided Structural Perturbation
por: Deng, Hao, et al.
Publicado: (2026)

Taming Extreme Tokens: Covariance-Aware GRPO with Gaussian-Kernel Advantage Reweighting
por: Wang, Cheng, et al.
Publicado: (2026)

An Adaptive Factorized Nyström Preconditioner for Regularized Kernel Matrices
por: Zhao, Shifan, et al.
Publicado: (2023)

APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games
por: Chen, Yifei, et al.
Publicado: (2025)

The inexact power augmented Lagrangian method for constrained nonconvex optimization
por: Bodard, Alexander, et al.
Publicado: (2024)