Cover Image

Robust principal component analysis with rank and cardinality regularization under matrix factorization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Wenjing, Bian, Wei, Toh, Kim-Chuan
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On solving a rank regularized minimization problem via equivalent factorized column-sparse regularized models
by: Li, Wenjing, et al.
Published: (2023)

Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
by: Lee, Ching-pei, et al.
Published: (2022)

On the B-subdifferential of proximal operators of affine-constrained $\ell_1$ regularizer
by: Li, Xudong, et al.
Published: (2025)

Wasserstein distributionally robust optimization and its tractable regularization formulations
by: Chu, Hong T. M., et al.
Published: (2024)

Stochastic Bregman Subgradient Methods for Nonsmooth Nonconvex Optimization Problems
by: Ding, Kuangyu, et al.
Published: (2024)

Inexact Bregman Proximal Gradient Method and its Inertial Variant with Absolute and Partial Relative Stopping Criteria
by: Yang, Lei, et al.
Published: (2021)

On the convergence rates of moment-SOS hierarchies approximation of truncated moment sequences
by: Tran, Hoang Anh, et al.
Published: (2025)

On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem
by: Ding, Kuangyu, et al.
Published: (2025)

An Inexact Bregman Proximal Difference-of-Convex Algorithm with Two Types of Relative Stopping Criteria
by: Yang, Lei, et al.
Published: (2024)

RiNNAL+: a Riemannian ALM Solver for SDP-RLT Relaxations of Mixed-Binary Quadratic Programs
by: Hou, Di, et al.
Published: (2025)

Exploring chordal sparsity in semidefinite programming with sparse plus low-rank data matrices
by: Tang, Tianyun, et al.
Published: (2024)

Nonsmooth rank-one symmetric matrix factorization landscape
by: Josz, Cédric, et al.
Published: (2024)

Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
by: Ding, Kuangyu, et al.
Published: (2023)

Low-rank approximated Kalman filter using Oja's principal component flow for discrete-time linear systems
by: Tsuzuki, Daiki, et al.
Published: (2024)

On the efficient computation of proximal operators of affine-constrained nonconvex functions
by: Hou, Di, et al.
Published: (2026)

ripALM: A Relative-Type Inexact Proximal Augmented Lagrangian Method for Linearly Constrained Convex Optimization
by: Zhu, Jiayi, et al.
Published: (2024)

An Exact Penalty Approach for Equality Constrained Optimization over a Convex Set
by: Xiao, Nachuan, et al.
Published: (2025)

Learning-rate-free Momentum SGD with Reshuffling Converges in Nonsmooth Nonconvex Optimization
by: Hu, Xiaoyin, et al.
Published: (2024)

Partial Envelope for Optimization Problem with Nonconvex Constraints
by: Hu, Xiaoyin, et al.
Published: (2025)

Convergence Analysis of a Relative-type Inexact Preconditioned Proximal ALM for Convex Nonlinear Programming
by: Yang, Lei, et al.
Published: (2025)

Adaptive sieving: A dimension reduction technique for sparse optimization problems
by: Yuan, Yancheng, et al.
Published: (2023)

A Hybrid Subgradient Method for Nonsmooth Nonconvex Bilevel Optimization
by: Xiao, Nachuan, et al.
Published: (2025)

A Quadratically Convergent Alternating Projection Method for Nonconvex Sets
by: Xiao, Nachuan, et al.
Published: (2025)

A Minimization Approach for Minimax Optimization with Coupled Constraints
by: Hu, Xiaoyin, et al.
Published: (2024)

Low-rank approximated Kalman-Bucy filters using Oja's principal component flow for linear time-invariant systems
by: Tsuzuki, Daiki, et al.
Published: (2024)

Learning Graph Laplacian with MCP
by: Zhang, Yangjing, et al.
Published: (2020)

Improved Rates for Stochastic Variance-Reduced Difference-of-Convex Algorithms
by: Nguyen, Anh Duc, et al.
Published: (2025)

A Low-rank Augmented Lagrangian Method for Polyhedral-SDP and Moment-SOS Relaxations of Polynomial Optimization
by: Hou, Di, et al.
Published: (2025)

A low-rank augmented Lagrangian method for doubly nonnegative relaxations of mixed-binary quadratic programs
by: Hou, Di, et al.
Published: (2025)

Tensor factorization based method for low rank matrix completion and its application on tensor completion
by: Yu, Quan, et al.
Published: (2022)

Optimization Hyper-parameter Laws for Large Language Models
by: Xie, Xingyu, et al.
Published: (2024)

Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees
by: Xiao, Nachuan, et al.
Published: (2023)

Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization
by: Xiao, Nachuan, et al.
Published: (2024)

LoCo: Low-Bit Communication Adaptor for Large-scale Model Training
by: Xie, Xingyu, et al.
Published: (2024)

CDOpt: A Python Package for a Class of Riemannian Optimization
by: Xiao, Nachuan, et al.
Published: (2022)

Stochastic Subgradient Methods with Guaranteed Global Stability in Nonsmooth Nonconvex Optimization
by: Xiao, Nachuan, et al.
Published: (2023)

On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models
by: Zhang, Yangjing, et al.
Published: (2022)

Tight SDP relaxations for cardinality-constrained problems
by: Wiegele, Angelika, et al.
Published: (2021)

Explicit MPC for the constrained zonotope case with low-rank matrix updates
by: Mihai, Stefan S., et al.
Published: (2025)

Computing all Nash equilibria of low-rank bi-matrix games
by: Feinstein, Zachary, et al.
Published: (2025)