Copertina

Provable Phase Retrieval with Mirror Descent

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Godeme, Jean-Jacques, Fadili, Jalal, Buet, Xavier, Zerrad, Myriam, Lequime, Michel, Amra, Claude
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Optimization and Control Computer Vision and Pattern Recognition Information Theory
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Stable Phase Retrieval with Mirror Descent
di: Godeme, Jean-Jacques, et al.
Pubblicazione: (2024)

Low Complexity Regularized Phase Retrieval
di: Godeme, Jean-Jacques, et al.
Pubblicazione: (2024)

A Fast and Provable Algorithm for Sparse Phase Retrieval
di: Cai, Jian-Feng, et al.
Pubblicazione: (2023)

Inertial Bregman Proximal Gradient under Partial Smoothness
di: Godeme, Jean-Jacques
Pubblicazione: (2025)

Differentiation of inertial methods for optimizing smooth parametric function
di: Godeme, Jean-Jacques
Pubblicazione: (2025)

Controlled Optimization of Quadratic Functions in $\mathbb{R}^n$
di: Godeme, Jean-Jacques
Pubblicazione: (2025)

A Mirror-Descent Algorithm for Computing the Petz-Rényi Capacity of Classical-Quantum Channels
di: Lai, Yu-Hong, et al.
Pubblicazione: (2026)

Deterministic Zeroth-Order Mirror Descent via Vector Fields with A Posteriori Certification
di: Hayashi, Masahito
Pubblicazione: (2026)

Phasebook: A Survey of Selected Open Problems in Phase Retrieval
di: Allain, Marc, et al.
Pubblicazione: (2025)

Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
di: Fridovich-Keil, Sara, et al.
Pubblicazione: (2023)

Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent
di: Yang, Tong, et al.
Pubblicazione: (2025)

Structured Gradient Descent for Fast Robust Low-Rank Hankel Matrix Completion
di: Cai, HanQin, et al.
Pubblicazione: (2022)

EVODiff: Entropy-aware Variance Optimized Diffusion Inference
di: Li, Shigui, et al.
Pubblicazione: (2025)

Inertial Quasi-Newton Methods for Monotone Inclusion: Efficient Resolvent Calculus and Primal-Dual Methods
di: Wang, Shida, et al.
Pubblicazione: (2022)

Global non-asymptotic super-linear convergence rates of regularized proximal quasi-Newton methods on non-smooth composite problems
di: Wang, Shida, et al.
Pubblicazione: (2024)

Convergence rates of regularized quasi-Newton methods without strong convexity
di: Wang, Shida, et al.
Pubblicazione: (2025)

Stochastic Monotone Inclusion with Closed Loop Distributions
di: Ennaji, Hamza, et al.
Pubblicazione: (2024)

The stochastic Ravine accelerated gradient method with general extrapolation coefficients
di: Attouch, Hedy, et al.
Pubblicazione: (2024)

A Quasi-Newton Primal-Dual Algorithm with Line Search
di: Wang, Shida, et al.
Pubblicazione: (2024)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
di: Shen, Wei, et al.
Pubblicazione: (2023)

Holographic Phase Retrieval and Reference Design
di: Barmherzig, David A., et al.
Pubblicazione: (2019)

An SDE perspective on stochastic convex optimization
di: Maulen-Soto, Rodrigo, et al.
Pubblicazione: (2022)

Online Riemannian Gradient Descent for Quantum State Tomography with Matrix Product Operators
di: Cai, Jian-Feng, et al.
Pubblicazione: (2026)

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
di: Sucker, Michael, et al.
Pubblicazione: (2024)

Inexact and Stochastic Gradient Optimization Algorithms with Inertia and Hessian Driven Damping
di: Choudhary, Harsh, et al.
Pubblicazione: (2025)

The Local Landscape of Phase Retrieval Under Limited Samples
di: Liu, Kaizhao, et al.
Pubblicazione: (2023)

The Iterates of Nesterov's Accelerated Algorithm Converge in The Critical Regimes
di: Bot, Radu Ioan, et al.
Pubblicazione: (2025)

Solution uniqueness of convex optimization problems via the radial cone
di: Fadili, Jalal, et al.
Pubblicazione: (2024)

Accelerating Convergence of Score-Based Diffusion Models, Provably
di: Li, Gen, et al.
Pubblicazione: (2024)

A connection between Tempering and Entropic Mirror Descent
di: Chopin, Nicolas, et al.
Pubblicazione: (2023)

Target Mirror Descent: A Unifying Framework for Solving Monotone Variational Inequalities
di: Chen, Yu-Wen, et al.
Pubblicazione: (2026)

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
di: Alfano, Carlo, et al.
Pubblicazione: (2023)

Provably Convergent Plug & Play Linearized ADMM, applied to Deblurring Spatially Varying Kernels
di: Laroche, Charles, et al.
Pubblicazione: (2022)

Mirror Descent for Deterministic Optimal Control
di: Feng, Ye, et al.
Pubblicazione: (2026)

A Unified Variational Design of Predictive Mirror Descent in Convex Games under Stochastic Feedback
di: Pan, Yunian, et al.
Pubblicazione: (2026)

The incomplete Analytic Hierarchy Process and Bradley-Terry model: (in)consistency and information retrieval
di: Gyarmati, László, et al.
Pubblicazione: (2022)

A wonderful triangle in compressed sensing
di: Wang, Jun
Pubblicazione: (2022)

Efficient URLLC with a Reconfigurable Intelligent Surface and Imperfect Device Tracking
di: Saggese, Fabio, et al.
Pubblicazione: (2022)

Beyond-Diagonal RIS For Enhanced Secrecy and Sensing Gains in Secure ISAC Networks: An Optimization Framework
di: Illi, Elmehdi, et al.
Pubblicazione: (2026)

Radon random sampling and reconstruction in local shift-invariant signal space
di: Deng, Zhanpeng, et al.
Pubblicazione: (2025)