Copertina

A Muon-Accelerated Algorithm for Low Separation Rank Tensor Generalized Linear Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liang, Xiao, Li, Shuang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Signal Processing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

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

Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling
di: Schynol, Lukas, et al.
Pubblicazione: (2024)

Low-Rank Adaptation Redux for Large Models
di: Li, Bingcong, et al.
Pubblicazione: (2026)

Normalized Iterative Hard Thresholding for Tensor Recovery
di: Li, Li, et al.
Pubblicazione: (2025)

When Bayesian Tensor Completion Meets Multioutput Gaussian Processes: Functional Universality and Rank Learning
di: Li, Siyuan, et al.
Pubblicazione: (2025)

Revisiting Trace Norm Minimization for Tensor Tucker Completion: A Direct Multilinear Rank Learning Approach
di: Tong, Xueke, et al.
Pubblicazione: (2024)

Noisy Low Rank Column-wise Sensing
di: Singh, Ankit Pratap, et al.
Pubblicazione: (2024)

Efficient Federated Low Rank Matrix Completion
di: Abbasi, Ahmed Ali, et al.
Pubblicazione: (2024)

Personalized Coupled Tensor Decomposition for Multimodal Data Fusion: Uniqueness and Algorithms
di: Borsoi, Ricardo Augusto, et al.
Pubblicazione: (2024)

Landscape Analysis of Simultaneous Blind Deconvolution and Phase Retrieval via Structured Low-Rank Tensor Recovery
di: Liang, Xiao, et al.
Pubblicazione: (2025)

Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach
di: Liang, Yuchen, et al.
Pubblicazione: (2024)

Low-Rank Matrix Factorizations with Volume-based Constraints and Regularizations
di: Thanh, Olivier Vu
Pubblicazione: (2024)

SPaRSe-TIME: Saliency-Projected Low-Rank Temporal Modeling for Efficient and Interpretable Time Series Prediction
di: Shahriar, K. A.
Pubblicazione: (2026)

Low Rank and Sparse Fourier Structure in Recurrent Networks Trained on Modular Addition
di: Rangamani, Akshay
Pubblicazione: (2025)

Learning to Separate RF Signals Under Uncertainty: Detect-Then-Separate vs. Unified Joint Models
di: Rodrigez, Ariel, et al.
Pubblicazione: (2026)

Robust Tensor Completion via Gradient Tensor Nulclear L1-L2 Norm for Traffic Data Recovery
di: Shu, Hao, et al.
Pubblicazione: (2025)

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

Exact Tensor Completion Powered by Slim Transforms
di: Ge, Li, et al.
Pubblicazione: (2024)

Generalized Nonnegative Structured Kruskal Tensor Regression
di: Wang, Xinjue, et al.
Pubblicazione: (2025)

EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters
di: Lotey, Taveena, et al.
Pubblicazione: (2024)

A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems
di: Ju, Haocheng, et al.
Pubblicazione: (2023)

PoLAR: Polar-Decomposed Low-Rank Adapter Representation
di: Lion, Kai, et al.
Pubblicazione: (2025)

An Adaptive Latent Factorization of Tensors Model for Embedding Dynamic Communication Network
di: Liao, Xin, et al.
Pubblicazione: (2024)

A Context Augmented Multi-Play Multi-Armed Bandit Algorithm for Fast Channel Allocation in Opportunistic Spectrum Access
di: Li, Ruiyu, et al.
Pubblicazione: (2026)

Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting
di: Gupta, Divij, et al.
Pubblicazione: (2024)

An Overview of Low-Rank Structures in the Training and Adaptation of Large Models
di: Balzano, Laura, et al.
Pubblicazione: (2025)

The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
di: Xu, Xingyu, et al.
Pubblicazione: (2023)

A Weight-aware-based Multi-source Unsupervised Domain Adaptation Method for Human Motion Intention Recognition
di: Liu, Xiao-Yin, et al.
Pubblicazione: (2024)

A Nonlinear Acceleration Method for Iterative Algorithms
di: Shamsi, Mahdi, et al.
Pubblicazione: (2019)

Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
di: Yaras, Can, et al.
Pubblicazione: (2024)

Downlink MIMO Channel Estimation from Bits: Recoverability and Algorithm
di: Shrestha, Rajesh, et al.
Pubblicazione: (2024)

Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
di: Qin, Zhen, et al.
Pubblicazione: (2024)

Efficient Wireless Federated Learning via Low-Rank Gradient Factorization
di: Guo, Mingzhao, et al.
Pubblicazione: (2024)

Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks
di: Kang, Tianqu, et al.
Pubblicazione: (2024)

Robustness of Speech Separation Models for Similar-pitch Speakers
di: Lay, Bunlong, et al.
Pubblicazione: (2024)

Large-Scale Bayesian Tensor Reconstruction: An Approximate Message Passing Solution
di: Cheng, Bingyang, et al.
Pubblicazione: (2025)

Diffusion-based Generative Prior for Low-Complexity MIMO Channel Estimation
di: Fesl, Benedikt, et al.
Pubblicazione: (2024)

Efficient Patient Fine-Tuned Seizure Detection with a Tensor Kernel Machine
di: de Rooij, Seline J. S., et al.
Pubblicazione: (2024)

Adapting Tensor Kernel Machines to Enable Efficient Transfer Learning for Seizure Detection
di: de Rooij, Seline J. S., et al.
Pubblicazione: (2025)