Imagen de Portada

Score-Based Model for Low-Rank Tensor Recovery

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Cheng, Zhengyun, Wang, Changhao, Zhang, Guanwen, Xu, Yi, Zhou, Wei, Ji, Xiangyang
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Low-Rank Tensor Recovery via Variational Schatten-p Quasi-Norm and Jacobian Regularization
por: Cheng, Zhengyun, et al.
Publicado: (2025)

PromptMono: Cross Prompting Attention for Self-Supervised Monocular Depth Estimation in Challenging Environments
por: Wang, Changhao, et al.
Publicado: (2025)

Joint Tensor and Inter-View Low-Rank Recovery for Incomplete Multiview Clustering
por: Wang, Jianyu, et al.
Publicado: (2025)

Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent
por: Liu, Zhiyu, et al.
Publicado: (2024)

Efficient Generalized Low-Rank Tensor Contextual Bandits
por: Yi, Qianxin, et al.
Publicado: (2023)

Low-Rank Tensor Learning by Generalized Nonconvex Regularization
por: Xia, Sijia, et al.
Publicado: (2024)

Low-Rank Tensors for Multi-Dimensional Markov Models
por: Navarro, Madeline, et al.
Publicado: (2024)

Penalizing Localized Dirichlet Energies in Low Rank Tensor Products
por: Karakasis, Paris A., et al.
Publicado: (2026)

Robust Low-rank Tensor Train Recovery
por: Qin, Zhen, et al.
Publicado: (2024)

LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
por: Yang, Yifan, et al.
Publicado: (2024)

Statistical Inference for Low-Rank Tensor Models
por: Xu, Ke, et al.
Publicado: (2025)

Stochastic Weakly Convex Optimization Under Heavy-Tailed Noises
por: Zhu, Tianxi, et al.
Publicado: (2025)

Structure-Preserving Margin Distribution Learning for High-Order Tensor Data with Low-Rank Decomposition
por: Xu, Yang, et al.
Publicado: (2025)

Low-Rank Tensor Decompositions for the Theory of Neural Networks
por: Borsoi, Ricardo, et al.
Publicado: (2025)

Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks
por: Gao, Yihang, et al.
Publicado: (2025)

Low Rank Tensor Completion via Adaptive ADMM
por: Führling, Niclas, et al.
Publicado: (2026)

When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery
por: Xu, Shirong, et al.
Publicado: (2025)

Semi-supervised Symmetric Non-negative Matrix Factorization with Low-Rank Tensor Representation
por: Jia, Yuheng, et al.
Publicado: (2024)

Low-Rank Tensor Approximation of Weights in Large Language Models via Cosine Lanczos Bidiagonalization
por: Ichi, A. El, et al.
Publicado: (2026)

MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-tuning
por: Wang, Maolin, et al.
Publicado: (2025)

Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning
por: Rozada, Sergio, et al.
Publicado: (2025)

Addressing Finite-Horizon MDPs via Low-Rank Tensor Value Approximation
por: Rozada, Sergio, et al.
Publicado: (2025)

Dynamic Low-Rank Sparse Adaptation for Large Language Models
por: Huang, Weizhong, et al.
Publicado: (2025)

Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption
por: Cai, HanQin, et al.
Publicado: (2023)

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

Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
por: Jedra, Yassir, et al.
Publicado: (2024)

A Muon-Accelerated Algorithm for Low Separation Rank Tensor Generalized Linear Models
por: Liang, Xiao, et al.
Publicado: (2026)

Joint Bayesian Parameter and Model Order Estimation for Low-Rank Probability Mass Tensors
por: Chege, Joseph K., et al.
Publicado: (2024)

Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training
por: Zhou, Wenjie, et al.
Publicado: (2026)

LoTR: Low Tensor Rank Weight Adaptation
por: Bershatsky, Daniel, et al.
Publicado: (2024)

Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision Making
por: Zhou, Jie, et al.
Publicado: (2020)

Convolutionally Low-Rank Models with Modified Quantile Regression for Interval Time Series Forecasting
por: Zhu, Miaoxuan, et al.
Publicado: (2026)

Accelerating Large-Scale Regularized High-Order Tensor Recovery
por: Qin, Wenjin, et al.
Publicado: (2025)

A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning
por: Rozada, Sergio, et al.
Publicado: (2025)

Joint Tensor-Train Parameterization for Efficient and Expressive Low-Rank Adaptation
por: Qi, Jun, et al.
Publicado: (2025)

Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning
por: Rozada, Sergio, et al.
Publicado: (2022)

Efficient Low-Tubal-Rank Tensor Estimation via Alternating Preconditioned Gradient Descent
por: Liu, Zhiyu, et al.
Publicado: (2025)

Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters
por: Wang, Xinjue, et al.
Publicado: (2026)

Multi-Dimensional Visual Data Recovery: Scale-Aware Tensor Modeling and Accelerated Randomized Computation
por: Qin, Wenjin, et al.
Publicado: (2026)

NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models
por: Lin, Cheng, et al.
Publicado: (2024)