Stochastic Algorithms for Large-Scale Composite Optimization: the Case of Single-Shot X-FEL Imaging
Fuente:
arXiv
Saved in:
| Main Authors: | Luke, D. Russell, Schultze, Steffen, Grubmüller, Helmut |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
by: Dahl, Simeon vom, et al.
Published: (2026)
by: Dahl, Simeon vom, et al.
Published: (2026)
Fast Frank--Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
by: Takahashi, Shota, et al.
Published: (2025)
by: Takahashi, Shota, et al.
Published: (2025)
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
by: Milzarek, Andre, et al.
Published: (2022)
by: Milzarek, Andre, et al.
Published: (2022)
A Single-Loop Stochastic Proximal Quasi-Newton Method for Large-Scale Nonsmooth Convex Optimization
by: Song, Yongcun, et al.
Published: (2024)
by: Song, Yongcun, et al.
Published: (2024)
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
by: Higuchi, Rei, et al.
Published: (2024)
by: Higuchi, Rei, et al.
Published: (2024)
On Tackling High-Dimensional Nonconvex Stochastic Optimization via Stochastic First-Order Methods with Non-smooth Proximal Terms and Variance Reduction
by: Xie, Yue, et al.
Published: (2025)
by: Xie, Yue, et al.
Published: (2025)
Randomized block proximal method with locally Lipschitz continuous gradient
by: Pérez-Aros, Pedro, et al.
Published: (2025)
by: Pérez-Aros, Pedro, et al.
Published: (2025)
On a globally convergent semismooth* Newton method in nonsmooth nonconvex optimization
by: Gfrerer, H.
Published: (2024)
by: Gfrerer, H.
Published: (2024)
Convergence Conditions for Stochastic Line Search Based Optimization of Over-parametrized Models
by: Lapucci, Matteo, et al.
Published: (2024)
by: Lapucci, Matteo, et al.
Published: (2024)
Stochastic Optimization under Hidden Convexity
by: Fatkhullin, Ilyas, et al.
Published: (2023)
by: Fatkhullin, Ilyas, et al.
Published: (2023)
A Stochastic Gradient Descent Method for Globally Minimizing Nearly Convex Functions
by: Bao, Chenglong, et al.
Published: (2025)
by: Bao, Chenglong, et al.
Published: (2025)
Effectively Leveraging Momentum Terms in Stochastic Line Search Frameworks for Fast Optimization of Finite-Sum Problems
by: Lapucci, Matteo, et al.
Published: (2024)
by: Lapucci, Matteo, et al.
Published: (2024)
Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
by: Deng, Kangkang, et al.
Published: (2024)
by: Deng, Kangkang, et al.
Published: (2024)
Accelerated Natural Gradient Method for Parametric Manifold Optimization
by: Li, Chenyi, et al.
Published: (2025)
by: Li, Chenyi, et al.
Published: (2025)
A globalization of L-BFGS and the Barzilai-Borwein method for nonconvex unconstrained optimization
by: Mannel, Florian
Published: (2024)
by: Mannel, Florian
Published: (2024)
Range of optimal values in absolute value linear programming with interval data
by: Hladík, Milan
Published: (2025)
by: Hladík, Milan
Published: (2025)
Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization
by: Xie, Yue, et al.
Published: (2024)
by: Xie, Yue, et al.
Published: (2024)
A structured L-BFGS method and its application to inverse problems
by: Mannel, Florian, et al.
Published: (2023)
by: Mannel, Florian, et al.
Published: (2023)
A structured L-BFGS method with diagonal scaling and its application to image registration
by: Mannel, Florian, et al.
Published: (2024)
by: Mannel, Florian, et al.
Published: (2024)
Asymptotic Convergence and Stability of Adaptive Gradient Methods in Smooth Non-convex Optimization
by: Jin, Ruinan, et al.
Published: (2026)
by: Jin, Ruinan, et al.
Published: (2026)
Bregman Stochastic Proximal Point Algorithm with Variance Reduction
by: Traoré, Cheik, et al.
Published: (2025)
by: Traoré, Cheik, et al.
Published: (2025)
Heavy-ball Differential Equation Achieves $O(\varepsilon^{-7/4})$ Convergence for Nonconvex Functions
by: Okamura, Kaito, et al.
Published: (2024)
by: Okamura, Kaito, et al.
Published: (2024)
Stability and convergence analysis of AdaGrad for non-convex optimization via novel stopping time-based techniques
by: Jin, Ruinan, et al.
Published: (2024)
by: Jin, Ruinan, et al.
Published: (2024)
Bilevel Learning via Inexact Stochastic Gradient Descent
by: Salehi, Mohammad Sadegh, et al.
Published: (2025)
by: Salehi, Mohammad Sadegh, et al.
Published: (2025)
Shuffling the Stochastic Mirror Descent via Dual Lipschitz Continuity and Kernel Conditioning
by: Qiu, Junwen, et al.
Published: (2026)
by: Qiu, Junwen, et al.
Published: (2026)
A new envelope function for nonsmooth DC optimization
by: Themelis, Andreas, et al.
Published: (2020)
by: Themelis, Andreas, et al.
Published: (2020)
On convergence of a $q$-random coordinate constrained algorithm for non-convex problems
by: Ghaffari-Hadigheh, Alireza, et al.
Published: (2022)
by: Ghaffari-Hadigheh, Alireza, et al.
Published: (2022)
Spectrally Constrained Optimization
by: Garner, Casey, et al.
Published: (2023)
by: Garner, Casey, et al.
Published: (2023)
Local Convergence Analysis of ADMM for Nonconvex Composite Optimization
by: Xie, Xiyuan, et al.
Published: (2026)
by: Xie, Xiyuan, et al.
Published: (2026)
Decentralized projected Riemannian stochastic recursive momentum method for nonconvex optimization
by: Deng, Kangkang, et al.
Published: (2024)
by: Deng, Kangkang, et al.
Published: (2024)
General Constrained Matrix Optimization
by: Garner, Casey, et al.
Published: (2024)
by: Garner, Casey, et al.
Published: (2024)
A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods
by: Qiu, Junwen, et al.
Published: (2024)
by: Qiu, Junwen, et al.
Published: (2024)
An Algebraically Converging Stochastic Gradient Descent Algorithm for Global Optimization
by: Engquist, Björn, et al.
Published: (2022)
by: Engquist, Björn, et al.
Published: (2022)
MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization
by: Li, Luxuan, et al.
Published: (2026)
by: Li, Luxuan, et al.
Published: (2026)
The Augmented Mixing Method: Computing High-Accuracy Primal-Dual Solutions to Large-Scale SDPs via Column Updates
by: Brosch, Daniel, et al.
Published: (2025)
by: Brosch, Daniel, et al.
Published: (2025)
cuHALLaR: A GPU Accelerated Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming
by: Aguirre, Jacob M., et al.
Published: (2025)
by: Aguirre, Jacob M., et al.
Published: (2025)
A MINRES-based Linesearch Algorithm for Nonconvex Optimization with Non-positive Curvature Detection
by: Zeng, Hanfeng, et al.
Published: (2026)
by: Zeng, Hanfeng, et al.
Published: (2026)
Inexact Limited Memory Bundle Method
by: Lampainen, Jenni, et al.
Published: (2026)
by: Lampainen, Jenni, et al.
Published: (2026)
An efficient asymptotic DC method for sparse and low-rank matrix recovery
by: Ding, Mingcai, et al.
Published: (2024)
by: Ding, Mingcai, et al.
Published: (2024)
Reinforcement-learning-based Algorithms for Optimization Problems and Applications to Inverse Problems
by: Xu, Chen, et al.
Published: (2023)
by: Xu, Chen, et al.
Published: (2023)
Similar Items
-
Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
by: Dahl, Simeon vom, et al.
Published: (2026) -
Fast Frank--Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
by: Takahashi, Shota, et al.
Published: (2025) -
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
by: Milzarek, Andre, et al.
Published: (2022) -
A Single-Loop Stochastic Proximal Quasi-Newton Method for Large-Scale Nonsmooth Convex Optimization
by: Song, Yongcun, et al.
Published: (2024) -
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
by: Higuchi, Rei, et al.
Published: (2024)