An Efficient High-Dimensional Gradient Estimator for Stochastic Differential Equations
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Shengbo, Blanchet, Jose, Glynn, Peter |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Optimal Sample Complexity for Average Reward Markov Decision Processes
por: Wang, Shengbo, et al.
Publicado: (2023)
por: Wang, Shengbo, et al.
Publicado: (2023)
Computable Bounds on Convergence of Markov Chains in Wasserstein Distance via Contractive Drift
por: Qu, Yanlin, et al.
Publicado: (2023)
por: Qu, Yanlin, et al.
Publicado: (2023)
Stochastic Modified Equations for Stochastic Gradient Descent in Infinite-Dimensional Hilbert Spaces
por: Cerrai, Sandra, et al.
Publicado: (2026)
por: Cerrai, Sandra, et al.
Publicado: (2026)
On the Foundation of Distributionally Robust Reinforcement Learning
por: Wang, Shengbo, et al.
Publicado: (2023)
por: Wang, Shengbo, et al.
Publicado: (2023)
Sample Complexity of Variance-reduced Distributionally Robust Q-learning
por: Wang, Shengbo, et al.
Publicado: (2023)
por: Wang, Shengbo, et al.
Publicado: (2023)
Linear Algebraic Truncation Algorithm with A Posteriori Error Bounds for Computing Markov Chain Equilibrium Gradients
por: Mahdian, Saied, et al.
Publicado: (2025)
por: Mahdian, Saied, et al.
Publicado: (2025)
Q-Measure-Learning for Continuous State RL: Efficient Implementation and Convergence
por: Wang, Shengbo
Publicado: (2026)
por: Wang, Shengbo
Publicado: (2026)
Infinite Anticipation Backward Stochastic Differential Equations
por: Cheng, Guanwei, et al.
Publicado: (2025)
por: Cheng, Guanwei, et al.
Publicado: (2025)
Stochastic Passivity in Stochastic Differential Equations: A Port-Hamiltonian Perspective
por: Ackermann, Julia, et al.
Publicado: (2025)
por: Ackermann, Julia, et al.
Publicado: (2025)
Spatially Controlled Evolution of Composite Materials via Stochastic Partial Differential Equations
por: Agram, Nacira, et al.
Publicado: (2025)
por: Agram, Nacira, et al.
Publicado: (2025)
An Optimization-Based Framework for Solving Forward-Backward Stochastic Differential Equations: Convergence Analysis and Error Bounds
por: Wang, Yutian, et al.
Publicado: (2025)
por: Wang, Yutian, et al.
Publicado: (2025)
A Communication-Efficient Stochastic Gradient Descent Algorithm for Distributed Nonconvex Optimization
por: Xie, Antai, et al.
Publicado: (2024)
por: Xie, Antai, et al.
Publicado: (2024)
Picard Iteration for Parameter Estimation in Nonlinear Ordinary Differential Equations
por: Talitckii, Aleksandr, et al.
Publicado: (2024)
por: Talitckii, Aleksandr, et al.
Publicado: (2024)
Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets
por: Yang, Yuchen, et al.
Publicado: (2024)
por: Yang, Yuchen, et al.
Publicado: (2024)
Distributionally Robust Regret Optimal LQR with Common Stage-Law Ambiguity
por: Fiechtner, Lukas-Benedikt, et al.
Publicado: (2026)
por: Fiechtner, Lukas-Benedikt, et al.
Publicado: (2026)
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
por: Keane, Ronan
Publicado: (2024)
por: Keane, Ronan
Publicado: (2024)
On the Convergence and Complexity of the Stochastic Central Finite-Difference Based Gradient Estimation Methods
por: Bollapragada, Raghu, et al.
Publicado: (2025)
por: Bollapragada, Raghu, et al.
Publicado: (2025)
High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
por: Yang, Yuchen, et al.
Publicado: (2025)
por: Yang, Yuchen, et al.
Publicado: (2025)
Highly Efficient Optimal Control for Lyophilization via Simulation of Discrete/Continuous Mixed-index Differential-algebraic Equations
por: Srisuma, Prakitr, et al.
Publicado: (2025)
por: Srisuma, Prakitr, et al.
Publicado: (2025)
Indefinite Linear-Quadratic Optimal Control Problems of Backward Stochastic Differential Equations with Partial Information
por: Li, Jialong, et al.
Publicado: (2025)
por: Li, Jialong, et al.
Publicado: (2025)
High-Probability Guarantees for Random Zeroth-Order (Stochastic) Gradient Descent
por: Ye, Haishan
Publicado: (2026)
por: Ye, Haishan
Publicado: (2026)
A Hessian-Aware Stochastic Differential Equation for Modelling SGD
por: Li, Xiang, et al.
Publicado: (2024)
por: Li, Xiang, et al.
Publicado: (2024)
Peng's Maximum Principle for Stochastic Delay Differential Equations of Mean-Field Type
por: Guatteri, Giuseppina, et al.
Publicado: (2025)
por: Guatteri, Giuseppina, et al.
Publicado: (2025)
Necessary and Sufficient Conditions for Optimal Control of Semilinear Stochastic Partial Differential Equations
por: Stannat, Wilhelm, et al.
Publicado: (2021)
por: Stannat, Wilhelm, et al.
Publicado: (2021)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
por: Li, Tianyou, et al.
Publicado: (2023)
por: Li, Tianyou, et al.
Publicado: (2023)
Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games
por: Sharpless, William, et al.
Publicado: (2024)
por: Sharpless, William, et al.
Publicado: (2024)
Almost Sure Convergence Analysis of Differentially Private Stochastic Gradient Methods
por: Mukherjee, Amartya, et al.
Publicado: (2025)
por: Mukherjee, Amartya, et al.
Publicado: (2025)
Carleman Estimates for Backward Anisotropic Stochastic Parabolic Equations with General Dynamic Boundary Conditions and Applications
por: Boulite, Said, et al.
Publicado: (2025)
por: Boulite, Said, et al.
Publicado: (2025)
Generalized Stochastic Gradient Descent with Momentum Methods for Smooth Optimization
por: Wang, Zimeng, et al.
Publicado: (2026)
por: Wang, Zimeng, et al.
Publicado: (2026)
Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence
por: Bonalli, Riccardo, et al.
Publicado: (2023)
por: Bonalli, Riccardo, et al.
Publicado: (2023)
Distributed Riemannian Stochastic Gradient Tracking Algorithm on the Stiefel Manifold
por: Zhao, Jishu, et al.
Publicado: (2024)
por: Zhao, Jishu, et al.
Publicado: (2024)
Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
por: Huynh, Phuoc-Toan, et al.
Publicado: (2026)
por: Huynh, Phuoc-Toan, et al.
Publicado: (2026)
High Probability Convergence Bounds for Non-convex Stochastic Gradient Descent with Sub-Weibull Noise
por: Madden, Liam, et al.
Publicado: (2020)
por: Madden, Liam, et al.
Publicado: (2020)
Compressed Distributed Stochastic Nonconvex Optimization with Differential Privacy
por: Xie, Antai, et al.
Publicado: (2026)
por: Xie, Antai, et al.
Publicado: (2026)
S-DIGing: A Stochastic Gradient Tracking Algorithm for Distributed Optimization
por: Li, Huaqing, et al.
Publicado: (2019)
por: Li, Huaqing, et al.
Publicado: (2019)
Distributed Adaptive Gradient Algorithm with Gradient Tracking for Stochastic Non-Convex Optimization
por: Han, Dongyu, et al.
Publicado: (2024)
por: Han, Dongyu, et al.
Publicado: (2024)
Universal Gradient Methods for Stochastic Convex Optimization
por: Rodomanov, Anton, et al.
Publicado: (2024)
por: Rodomanov, Anton, et al.
Publicado: (2024)
Improved Performance of Stochastic Gradients with Gaussian Smoothing
por: Starnes, Andrew, et al.
Publicado: (2023)
por: Starnes, Andrew, et al.
Publicado: (2023)
Convergence of the Iterates of the Stochastic Proximal Gradient Method
por: Madariaga, Javier I.
Publicado: (2026)
por: Madariaga, Javier I.
Publicado: (2026)
Differentially Private High Dimensional Bandits
por: Shukla, Apurv
Publicado: (2024)
por: Shukla, Apurv
Publicado: (2024)
Ejemplares similares
-
Optimal Sample Complexity for Average Reward Markov Decision Processes
por: Wang, Shengbo, et al.
Publicado: (2023) -
Computable Bounds on Convergence of Markov Chains in Wasserstein Distance via Contractive Drift
por: Qu, Yanlin, et al.
Publicado: (2023) -
Stochastic Modified Equations for Stochastic Gradient Descent in Infinite-Dimensional Hilbert Spaces
por: Cerrai, Sandra, et al.
Publicado: (2026) -
On the Foundation of Distributionally Robust Reinforcement Learning
por: Wang, Shengbo, et al.
Publicado: (2023) -
Sample Complexity of Variance-reduced Distributionally Robust Q-learning
por: Wang, Shengbo, et al.
Publicado: (2023)