A Bregman firmly nonexpansive proximal operator for baryconvex optimization
Fuente:
arXiv
Saved in:
| Main Author: | Achab, Mastane |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An inexact Bregman proximal point method and its acceleration version for unbalanced optimal transport
by: Chen, Xiang, et al.
Published: (2024)
by: Chen, Xiang, et al.
Published: (2024)
Bregman Douglas-Rachford Splitting Method
by: Ma, Shiqian, et al.
Published: (2025)
by: Ma, Shiqian, et al.
Published: (2025)
Online Nonconvex Bilevel Optimization with Bregman Divergences
by: Bohne, Jason, et al.
Published: (2024)
by: Bohne, Jason, et al.
Published: (2024)
Robust Sublinear Convergence Rates for Iterative Bregman Projections
by: Peyré, Gabriel
Published: (2026)
by: Peyré, Gabriel
Published: (2026)
Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms
by: Chen, He, et al.
Published: (2024)
by: Chen, He, et al.
Published: (2024)
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
by: Ding, Kuangyu, et al.
Published: (2023)
by: Ding, Kuangyu, et al.
Published: (2023)
Bregman Linearized Augmented Lagrangian Method for Nonconvex Constrained Stochastic Zeroth-order Optimization
by: Shi, Qiankun, et al.
Published: (2025)
by: Shi, Qiankun, et al.
Published: (2025)
Variable Bregman Majorization-Minimization Algorithm and its Application to Dirichlet Maximum Likelihood Estimation
by: Martin, Ségolène, et al.
Published: (2025)
by: Martin, Ségolène, et al.
Published: (2025)
Symmetrizing Bregman Divergence on the Cone of Positive Definite Matrices: Which Mean to Use and Why
by: Sial, Tushar, et al.
Published: (2026)
by: Sial, Tushar, et al.
Published: (2026)
Delay-tolerant distributed Bregman proximal algorithms
by: Chraibi, S., et al.
Published: (2024)
by: Chraibi, S., et al.
Published: (2024)
Sparse Polyak with optimal thresholding operators for high-dimensional M-estimation
by: Qiao, Tianqi, et al.
Published: (2025)
by: Qiao, Tianqi, et al.
Published: (2025)
Variance reduction techniques for stochastic proximal point algorithms
by: Traoré, Cheik, et al.
Published: (2023)
by: Traoré, Cheik, et al.
Published: (2023)
Efficient algorithms for implementing incremental proximal-point methods
by: Shtoff, Alex
Published: (2022)
by: Shtoff, Alex
Published: (2022)
Linear convergence of proximal descent schemes on the Wasserstein space
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
Mean-square and linear convergence of a stochastic proximal point algorithm in metric spaces of nonpositive curvature
by: Pischke, Nicholas
Published: (2025)
by: Pischke, Nicholas
Published: (2025)
Learning to optimize: A tutorial for continuous and mixed-integer optimization
by: Chen, Xiaohan, et al.
Published: (2024)
by: Chen, Xiaohan, et al.
Published: (2024)
Robotic warehousing operations: a learn-then-optimize approach to large-scale neighborhood search
by: Barnhart, Cynthia, et al.
Published: (2024)
by: Barnhart, Cynthia, et al.
Published: (2024)
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023)
by: Li, Tianjiao, et al.
Published: (2023)
BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantification
by: Lu, Yen-An, et al.
Published: (2024)
by: Lu, Yen-An, et al.
Published: (2024)
Bregman level proximal subdifferentials and new characterizations of Bregman proximal operators
by: Wang, Ziyuan, et al.
Published: (2025)
by: Wang, Ziyuan, et al.
Published: (2025)
Bregman three-operator splitting methods
by: Jiang, Xin, et al.
Published: (2022)
by: Jiang, Xin, et al.
Published: (2022)
A survey on secure decentralized optimization and learning
by: Liu, Changxin, et al.
Published: (2024)
by: Liu, Changxin, et al.
Published: (2024)
A new perspective on low-rank optimization
by: Bertsimas, Dimitris, et al.
Published: (2021)
by: Bertsimas, Dimitris, et al.
Published: (2021)
A note on convergence of Wasserstein policy optimization
by: Šiška, David, et al.
Published: (2026)
by: Šiška, David, et al.
Published: (2026)
A stochastic gradient method for trilevel optimization
by: Giovannelli, Tommaso, et al.
Published: (2025)
by: Giovannelli, Tommaso, et al.
Published: (2025)
Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimization
by: Mayfrank, Daniel, et al.
Published: (2024)
by: Mayfrank, Daniel, et al.
Published: (2024)
qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling
by: Renganathan, Ashwin, et al.
Published: (2023)
by: Renganathan, Ashwin, et al.
Published: (2023)
A constrained optimization approach to improve robustness of neural networks
by: Zhao, Shudian, et al.
Published: (2024)
by: Zhao, Shudian, et al.
Published: (2024)
Restarted contractive operators to learn at equilibrium
by: Davy, Leo, et al.
Published: (2025)
by: Davy, Leo, et al.
Published: (2025)
Distributed optimization: designed for federated learning
by: Guo, Wenyou, et al.
Published: (2025)
by: Guo, Wenyou, et al.
Published: (2025)
Instance-optimal stochastic convex optimization: Can we improve upon sample-average and robust stochastic approximation?
by: Jiang, Liwei, et al.
Published: (2026)
by: Jiang, Liwei, et al.
Published: (2026)
A minimax optimal control approach for robust neural ODEs
by: Cipriani, Cristina, et al.
Published: (2023)
by: Cipriani, Cristina, et al.
Published: (2023)
Approximate Bregman proximal gradient algorithm with variable metric Armijo--Wolfe line search
by: Fujiki, Kiwamu, et al.
Published: (2025)
by: Fujiki, Kiwamu, et al.
Published: (2025)
Bregman proximal gradient method for linear optimization under entropic constraints
by: Briceño-Arias, Luis M., et al.
Published: (2025)
by: Briceño-Arias, Luis M., et al.
Published: (2025)
Bridging conformal prediction and scenario optimization
by: O'Sullivan, Niall, et al.
Published: (2025)
by: O'Sullivan, Niall, et al.
Published: (2025)
Derivatives of Stochastic Gradient Descent in parametric optimization
by: Iutzeler, Franck, et al.
Published: (2024)
by: Iutzeler, Franck, et al.
Published: (2024)
Non-geodesically-convex optimization in the Wasserstein space
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
Stochastic optimization with arbitrary recurrent data sampling
by: Powell, William G., et al.
Published: (2024)
by: Powell, William G., et al.
Published: (2024)
Derivative-free tree optimization for complex systems
by: Wei, Ye, et al.
Published: (2024)
by: Wei, Ye, et al.
Published: (2024)
Accelerating optimization over the space of probability measures
by: Chen, Shi, et al.
Published: (2023)
by: Chen, Shi, et al.
Published: (2023)
Similar Items
-
An inexact Bregman proximal point method and its acceleration version for unbalanced optimal transport
by: Chen, Xiang, et al.
Published: (2024) -
Bregman Douglas-Rachford Splitting Method
by: Ma, Shiqian, et al.
Published: (2025) -
Online Nonconvex Bilevel Optimization with Bregman Divergences
by: Bohne, Jason, et al.
Published: (2024) -
Robust Sublinear Convergence Rates for Iterative Bregman Projections
by: Peyré, Gabriel
Published: (2026) -
Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms
by: Chen, He, et al.
Published: (2024)