Cover Image

Simple Alternating Minimization Provably Solves Complete Dictionary Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liang, Geyu, Zhang, Gavin, Fattahi, Salar, Zhang, Richard Y.
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Signal Processing Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding the Implicit Regularization of Gradient Descent in Over-parameterized Models
by: Ma, Jianhao, et al.
Published: (2025)

Dictionary Learning under Symmetries via Group Representations
by: Ghosh, Subhroshekhar, et al.
Published: (2023)

Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification
by: Zhang, Gavin, et al.
Published: (2022)

Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
by: Zhang, Gavin, et al.
Published: (2025)

Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion
by: Ma, Jianhao, et al.
Published: (2024)

K-Deep Simplex: Deep Manifold Learning via Local Dictionaries
by: Tankala, Pranay, et al.
Published: (2020)

Alternating Direction Method of Multipliers for Nonlinear Matrix Decompositions
by: Awari, Atharva, et al.
Published: (2025)

On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
by: Wei, Yudong, et al.
Published: (2025)

On the Crucial Role of Initialization for Matrix Factorization
by: Li, Bingcong, et al.
Published: (2024)

Can Learning Be Explained By Local Optimality In Robust Low-rank Matrix Recovery?
by: Ma, Jianhao, et al.
Published: (2023)

ODELoRA: Training Low-Rank Adaptation by Solving Ordinary Differential Equations
by: Gao, Yihang, et al.
Published: (2026)

Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel
by: Suwandi, Richard Cornelius, et al.
Published: (2023)

A Provably-Correct and Robust Convex Model for Smooth Separable NMF
by: Pan, Junjun, et al.
Published: (2025)

Federated Learning Using Three-Operator ADMM
by: Kant, Shashi, et al.
Published: (2022)

Near-Optimal Solutions of Constrained Learning Problems
by: Elenter, Juan, et al.
Published: (2024)

Optimized Gradient Tracking for Decentralized Online Learning
by: Sharma, Shivangi Dubey, et al.
Published: (2023)

Wasserstein Distributionally Robust Online Learning
by: Chen, Guixian, et al.
Published: (2026)

Block Majorization Minimization with Extrapolation and Application to $β$-NMF
by: Hien, Le Thi Khanh, et al.
Published: (2024)

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

Quantum Neural Networks for Solving Power System Transient Simulation Problem
by: Soltaninia, Mohammadreza, et al.
Published: (2024)

Waveform Design for Optimal PSL Under Spectral and Unimodular Constraints via Alternating Minimization
by: Huang, Chin-Wei, et al.
Published: (2022)

Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks
by: Zhang, Aoran, et al.
Published: (2026)

Efficient algorithms for the Hadamard decomposition
by: Wertz, Samuel, et al.
Published: (2025)

Nonasymptotic Convergence Rates for Plug-and-Play Methods With MMSE Denoisers
by: Pritchard, Henry, et al.
Published: (2025)

Nonnegative Matrix Factorization in the Component-Wise L1 Norm for Sparse Data
by: Seraghiti, Giovanni, et al.
Published: (2026)

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

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

Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery
by: de Vazelhes, William, et al.
Published: (2023)

Limited Communications Distributed Optimization via Deep Unfolded Distributed ADMM
by: Noah, Yoav, et al.
Published: (2023)

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

ConvexECG: Lightweight and Explainable Neural Networks for Personalized, Continuous Cardiac Monitoring
by: Ansari, Rayan, et al.
Published: (2024)

Localized Distributional Robustness in Submodular Multi-Task Subset Selection
by: Kaya, Ege C., et al.
Published: (2024)

Accelerated First-Order Optimization under Nonlinear Constraints
by: Muehlebach, Michael, et al.
Published: (2023)

A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm
by: Leong, Oscar, et al.
Published: (2025)

Locality Regularized Reconstruction: Structured Sparsity and Delaunay Triangulations
by: Mueller, Marshall, et al.
Published: (2024)

Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
by: Qin, Zhen, et al.
Published: (2024)

A Scalable Factorization Approach for High-Order Structured Tensor Recovery
by: Qin, Zhen, et al.
Published: (2025)

Wasserstein Distributionally Robust Risk-Sensitive Estimation via Conditional Value-at-Risk
by: Taha, Feras Al, et al.
Published: (2026)

Convolutional Proximal Neural Networks and Plug-and-Play Algorithms
by: Hertrich, Johannes, et al.
Published: (2020)

Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses
by: Ma, Ziye, et al.
Published: (2024)