Imagen de Portada

Noisy phase retrieval from subgaussian measurements

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Peng, Haiyang, Han, Deren, Li, Linbin, Huang, Meng
Formato:	Preprint
Publicado:	2024
Materias:	Optimization and Control 90C26, 90C30, 94A12
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A distributed Douglas-Rachford splitting method for solving linear constrained multi-block weakly convex problems
por: Hu, Leyu, et al.
Publicado: (2024)

The Dantzig Selector: Sparse Signals Recovery via l_p-q Minimization
por: Li, Jie, et al.
Publicado: (2023)

NS-RGS: Newton-Schulz based Riemannian gradient method for orthogonal group synchronization
por: Peng, Haiyang, et al.
Publicado: (2026)

Global convergence of the subgradient method for robust signal recovery
por: Cai, Zesheng, et al.
Publicado: (2026)

A New Spectral Conjugate Subgradient Method with Application in Computed Tomography Image Reconstruction
por: Loreto, Milagros, et al.
Publicado: (2023)

On the Hardness of the $L_1-L_2$ Regularization Problem
por: Ouyang, Yuyuan, et al.
Publicado: (2024)

Nonconvex Deterministic Matrix Completion by Projected Gradient Descent Methods
por: Xu, Hang, et al.
Publicado: (2024)

Quotient Manifold Optimization for Spectral Compressed Sensing
por: Wang, Wenlong, et al.
Publicado: (2025)

A four-operator splitting algorithm for nonconvex and nonsmooth optimization
por: Alcantara, Jan Harold, et al.
Publicado: (2024)

Extending Linear Convergence of the Proximal Point Algorithm: The Quasar-Convex Case
por: de Brito, José, et al.
Publicado: (2025)

Star Quasiconvexity: a Unified Approach for Linear Convergence of First-Order Methods Beyond Convexity
por: Khanh, Phan Quoc, et al.
Publicado: (2025)

Splitting Proximal Point Algorithms for the Sum of Prox-Convex Functions
por: de Brito, Jose, et al.
Publicado: (2026)

A heavy-ball type curve search method for smooth convexly constrained optimization
por: Donnini, Federica, et al.
Publicado: (2026)

Characterizations of Strongly Quasiconvex Functions
por: Hadjisavvas, Nicolas, et al.
Publicado: (2025)

Optimization over convex polyhedra via Hadamard parametrizations
por: Tang, Tianyun, et al.
Publicado: (2024)

Lagrangian Reformulation for Nonconvex Optimization: Tailoring Problems to Specialized Solvers
por: Quintero, Rodolfo A., et al.
Publicado: (2024)

Effective Front-Descent Algorithms with Convergence Guarantees
por: Lapucci, Matteo, et al.
Publicado: (2024)

Combining Gradient Information and Primitive Directions for High-Performance Mixed-Integer Optimization
por: Lapucci, Matteo, et al.
Publicado: (2024)

A Globally Convergent Gradient Method with Momentum
por: Lapucci, Matteo, et al.
Publicado: (2024)

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
por: Higuchi, Rei, et al.
Publicado: (2024)

Projection-based curve pattern search for black-box optimization over smooth convex sets
por: Jia, Xiaoxi, et al.
Publicado: (2025)

A Surrogate Value Function Formulation for Bilevel Optimization
por: Xu, Mengwei, et al.
Publicado: (2025)

Derivative-Free Bilevel Optimization with Inexact Lower-Level Solutions
por: Cesaroni, Edoardo, et al.
Publicado: (2026)

Penalty decomposition derivative free method for the minimization of partially separable functions over a convex feasible set
por: Cecere, Francesco, et al.
Publicado: (2025)

Bound tightening in lifted formulations: (sub)solver-dependent impact on performance in RLT-based algorithms
por: González-Díaz, Julio, et al.
Publicado: (2025)

On convergence of a $q$-random coordinate constrained algorithm for non-convex problems
por: Ghaffari-Hadigheh, Alireza, et al.
Publicado: (2022)

Interval-Valued Optimization Problems for Strongly LU-E-Invex and Strongly LU-E-Preinvex Functions
por: Tauheed, et al.
Publicado: (2026)

A Complete Loss Landscape Analysis of Regularized Deep Matrix Factorization
por: Chen, Po, et al.
Publicado: (2025)

On Difference-of-SOS and Difference-of-Convex-SOS Decompositions for Polynomials
por: Niu, Yi-Shuai, et al.
Publicado: (2018)

Parabolic Approximation & Relaxation for MINLP
por: Göß, Adrian, et al.
Publicado: (2024)

Norm-induced Cuts: Outer Approximation for Lipschitzian Constraint Functions
por: Göß, Adrian, et al.
Publicado: (2024)

Clash of MINLP Relaxations: Piecewise Linear vs. Global Parabolic
por: Göß, Adrian
Publicado: (2026)

On Tackling High-Dimensional Nonconvex Stochastic Optimization via Stochastic First-Order Methods with Non-smooth Proximal Terms and Variance Reduction
por: Xie, Yue, et al.
Publicado: (2025)

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers
por: Menickelly, Matt, et al.
Publicado: (2023)

Benign landscapes of low-dimensional relaxations for orthogonal synchronization on general graphs
por: McRae, Andrew D., et al.
Publicado: (2023)

Hidden convexity of quadratic systems and its application to quadratic programming
por: Huy, Nguyen Quang, et al.
Publicado: (2026)

Riemannian Gradient Method with Momentum
por: Leggio, Filippo, et al.
Publicado: (2026)

A minimal face constant rank constraint qualification for reducible conic programming
por: Andreani, Roberto, et al.
Publicado: (2023)

New vector transport operators extending a Riemannian CG algorithm to generalized Stiefel manifold with low-rank applications
por: Wang, Xuejie, et al.
Publicado: (2023)

A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods
por: Qiu, Junwen, et al.
Publicado: (2024)