Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient
Fuente:
arXiv
Saved in:
| Main Authors: | Lim, Dong-Young, Neufeld, Ariel, Sabanis, Sotirios, Zhang, Ying |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024)
by: Liang, Luxu, et al.
Published: (2024)
Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
by: Chen, Zeyi, et al.
Published: (2025)
by: Chen, Zeyi, et al.
Published: (2025)
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
by: Lim, Dong-Young, et al.
Published: (2021)
by: Lim, Dong-Young, et al.
Published: (2021)
Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints
by: Neufeld, Ariel, et al.
Published: (2022)
by: Neufeld, Ariel, et al.
Published: (2022)
Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures
by: Neufeld, Ariel, et al.
Published: (2022)
by: Neufeld, Ariel, et al.
Published: (2022)
Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting
by: Neufeld, Ariel, et al.
Published: (2022)
by: Neufeld, Ariel, et al.
Published: (2022)
Error analysis for stochastic gradient optimization schemes using modified equations
by: Bréhier, Charles-Edouard, et al.
Published: (2024)
by: Bréhier, Charles-Edouard, et al.
Published: (2024)
Feasible approximation of matching equilibria for large-scale matching for teams problems
by: Neufeld, Ariel, et al.
Published: (2023)
by: Neufeld, Ariel, et al.
Published: (2023)
Convergence analysis for an implementable scheme to solve the linear-quadratic stochastic optimal control problem with stochastic wave equation
by: Chaudhary, Abhishek
Published: (2025)
by: Chaudhary, Abhishek
Published: (2025)
Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis
by: Bartl, Daniel, et al.
Published: (2024)
by: Bartl, Daniel, et al.
Published: (2024)
Flatness-Aware Stochastic Gradient Langevin Dynamics
by: Bruno, Stefano, et al.
Published: (2025)
by: Bruno, Stefano, et al.
Published: (2025)
On the convergence of stochastic variance reduced gradient for linear inverse problems
by: Jin, Bangti, et al.
Published: (2025)
by: Jin, Bangti, et al.
Published: (2025)
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
by: Bruno, Stefano, et al.
Published: (2023)
by: Bruno, Stefano, et al.
Published: (2023)
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
by: Bruno, Stefano, et al.
Published: (2025)
by: Bruno, Stefano, et al.
Published: (2025)
Deep learning algorithms for FBSDEs with jumps: Applications to option pricing and a MFG model for smart grids
by: Alasseur, Clémence, et al.
Published: (2024)
by: Alasseur, Clémence, et al.
Published: (2024)
Non-concave stochastic optimal control in finite discrete time under model uncertainty
by: Neufeld, Ariel, et al.
Published: (2024)
by: Neufeld, Ariel, et al.
Published: (2024)
The Performance Of The Unadjusted Langevin Algorithm Without Smoothness Assumptions
by: Johnston, Tim, et al.
Published: (2025)
by: Johnston, Tim, et al.
Published: (2025)
A stochastic preconditioned Douglas-Rachford splitting method for saddle-point problems
by: Dong, Yakun, et al.
Published: (2022)
by: Dong, Yakun, et al.
Published: (2022)
Deep learning based numerical approximation algorithms for stochastic partial differential equations
by: Beck, Christian, et al.
Published: (2020)
by: Beck, Christian, et al.
Published: (2020)
Multilevel Picard algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities
by: Neufeld, Ariel, et al.
Published: (2023)
by: Neufeld, Ariel, et al.
Published: (2023)
Multilevel Picard scheme for solving high-dimensional drift control problems with state constraints
by: Zhong, Yuan
Published: (2025)
by: Zhong, Yuan
Published: (2025)
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
by: Stollenwerk, Alexander, et al.
Published: (2024)
by: Stollenwerk, Alexander, et al.
Published: (2024)
Randomized coordinate gradient descent almost surely escapes strict saddle points
by: Chen, Ziang, et al.
Published: (2025)
by: Chen, Ziang, et al.
Published: (2025)
Inverse problems for stochastic partial differential equations
by: Lü, Qi, et al.
Published: (2024)
by: Lü, Qi, et al.
Published: (2024)
Modelling sand ripples in mine countermeasure simulations by means of stochastic optimal control
by: Blondeel, Philippe, et al.
Published: (2024)
by: Blondeel, Philippe, et al.
Published: (2024)
Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean--Vlasov stochastic differential equations
by: Neufeld, Ariel, et al.
Published: (2023)
by: Neufeld, Ariel, et al.
Published: (2023)
Multilevel Picard approximations for McKean-Vlasov stochastic differential equations with nonconstant diffusion
by: Neufeld, Ariel, et al.
Published: (2025)
by: Neufeld, Ariel, et al.
Published: (2025)
An approximate Itô-SDE based simulated annealing algorithm for multivariate design optimization problems
by: Batou, A.
Published: (2019)
by: Batou, A.
Published: (2019)
A New Look at the Ensemble Kalman Filter for Inverse Problems: Duality, Non-Asymptotic Analysis and Convergence Acceleration
by: Krishnanunni, C G, et al.
Published: (2026)
by: Krishnanunni, C G, et al.
Published: (2026)
Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms
by: Ha, Yunsoo, et al.
Published: (2024)
by: Ha, Yunsoo, et al.
Published: (2024)
Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
by: Hertrich, Johannes, et al.
Published: (2023)
by: Hertrich, Johannes, et al.
Published: (2023)
Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
by: Hertrich, Johannes, et al.
Published: (2022)
by: Hertrich, Johannes, et al.
Published: (2022)
Non-exchangeable evolutionary and mean field games and their applications
by: Yoshioka, H., et al.
Published: (2025)
by: Yoshioka, H., et al.
Published: (2025)
Linking PageRank, Time Reversal, and Policy Evaluation
by: Avrachenkov, Konstantin, et al.
Published: (2026)
by: Avrachenkov, Konstantin, et al.
Published: (2026)
An accelerated gradient method with adaptive restart for convex multiobjective optimization problems
by: Luo, Hao, et al.
Published: (2025)
by: Luo, Hao, et al.
Published: (2025)
Solving stochastic partial differential equations using neural networks in the Wiener chaos expansion
by: Neufeld, Ariel, et al.
Published: (2024)
by: Neufeld, Ariel, et al.
Published: (2024)
Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
by: Jin, Qinian, et al.
Published: (2024)
by: Jin, Qinian, et al.
Published: (2024)
Gradient-adjusted underdamped Langevin dynamics for sampling
by: Zuo, Xinzhe, et al.
Published: (2024)
by: Zuo, Xinzhe, et al.
Published: (2024)
Convergence of the deep BSDE method for stochastic control problems formulated through the stochastic maximum principle
by: Huang, Zhipeng, et al.
Published: (2024)
by: Huang, Zhipeng, et al.
Published: (2024)
DeepMartingale: Duality of the Optimal Stopping Problem with Expressivity and High-Dimensional Hedging
by: Ye, Junyan, et al.
Published: (2025)
by: Ye, Junyan, et al.
Published: (2025)
Similar Items
-
Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024) -
Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
by: Chen, Zeyi, et al.
Published: (2025) -
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
by: Lim, Dong-Young, et al.
Published: (2021) -
Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints
by: Neufeld, Ariel, et al.
Published: (2022) -
Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures
by: Neufeld, Ariel, et al.
Published: (2022)