Finite-Time Decoupled Convergence in Nonlinear Two-Time-Scale Stochastic Approximation
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Yuze, Li, Xiang, Zhang, Zhihua |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
by: Han, Yuze, et al.
Published: (2024)
by: Han, Yuze, et al.
Published: (2024)
Convergence Rate in Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence
by: Chen, Zixi, et al.
Published: (2025)
by: Chen, Zixi, et al.
Published: (2025)
Fast Nonlinear Two-Time-Scale Stochastic Approximation: Achieving $O(1/k)$ Finite-Sample Complexity
by: Doan, Thinh T.
Published: (2024)
by: Doan, Thinh T.
Published: (2024)
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
by: Haque, Shaan Ul, et al.
Published: (2023)
by: Haque, Shaan Ul, et al.
Published: (2023)
$O(1/k)$ Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
by: Chandak, Siddharth
Published: (2025)
by: Chandak, Siddharth
Published: (2025)
Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise
by: Chandak, Siddharth, et al.
Published: (2025)
by: Chandak, Siddharth, et al.
Published: (2025)
Central Limit Theorem for Two-Time-Scale Approximate Distributionally Robust RL
by: Wang, Shengbo, et al.
Published: (2026)
by: Wang, Shengbo, et al.
Published: (2026)
Heavy-Tailed and Long-Range Dependent Noise in Stochastic Approximation: A Finite-Time Analysis
by: Chandak, Siddharth, et al.
Published: (2026)
by: Chandak, Siddharth, et al.
Published: (2026)
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning
by: Zeng, Sihan, et al.
Published: (2024)
by: Zeng, Sihan, et al.
Published: (2024)
On the Convergence of Policy in Unregularized Policy Mirror Descent
by: Lin, Dachao, et al.
Published: (2022)
by: Lin, Dachao, et al.
Published: (2022)
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
by: Zeng, Sihan, et al.
Published: (2021)
by: Zeng, Sihan, et al.
Published: (2021)
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling
by: Zhu, Feng, et al.
Published: (2025)
by: Zhu, Feng, et al.
Published: (2025)
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
by: Ge, Yuze, et al.
Published: (2024)
by: Ge, Yuze, et al.
Published: (2024)
Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
by: Sahinoglu, Emre, et al.
Published: (2025)
by: Sahinoglu, Emre, et al.
Published: (2025)
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
by: Ren, Zhaolin, et al.
Published: (2023)
by: Ren, Zhaolin, et al.
Published: (2023)
Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
by: Qian, Xiaochi, et al.
Published: (2024)
by: Qian, Xiaochi, et al.
Published: (2024)
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
by: Adibi, Arman, et al.
Published: (2024)
by: Adibi, Arman, et al.
Published: (2024)
A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation
by: Mitra, Aritra
Published: (2024)
by: Mitra, Aritra
Published: (2024)
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
by: Zhang, Chenyu, et al.
Published: (2024)
by: Zhang, Chenyu, et al.
Published: (2024)
Theoretical Analysis on how Learning Rate Warmup Accelerates Convergence
by: Liu, Yuxing, et al.
Published: (2025)
by: Liu, Yuxing, et al.
Published: (2025)
Convergence Analysis of the PAGE Stochastic Algorithm for Weakly Convex Finite-Sum Optimization
by: Condat, Laurent, et al.
Published: (2025)
by: Condat, Laurent, et al.
Published: (2025)
Almost Sure Convergence Rates of Stochastic Approximation and Reinforcement Learning via a Poisson-Moreau Drift
by: Liu, Xinyu, et al.
Published: (2026)
by: Liu, Xinyu, et al.
Published: (2026)
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
by: Huo, Dongyan, et al.
Published: (2024)
by: Huo, Dongyan, et al.
Published: (2024)
A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
by: Lee, Wei-Cheng, et al.
Published: (2025)
by: Lee, Wei-Cheng, et al.
Published: (2025)
Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise
by: Blaser, Ethan, et al.
Published: (2024)
by: Blaser, Ethan, et al.
Published: (2024)
Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysis
by: Chandak, Siddharth
Published: (2025)
by: Chandak, Siddharth
Published: (2025)
Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence
by: Han, Yinbin, et al.
Published: (2024)
by: Han, Yinbin, et al.
Published: (2024)
A Regularized Online Newton Method for Stochastic Convex Bandits with Linear Vanishing Noise
by: Zhan, Jingxin, et al.
Published: (2025)
by: Zhan, Jingxin, et al.
Published: (2025)
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications
by: Hu, Jie, et al.
Published: (2024)
by: Hu, Jie, et al.
Published: (2024)
Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
by: Li, Haoyu, et al.
Published: (2025)
by: Li, Haoyu, et al.
Published: (2025)
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
by: Kwon, Jeongyeol, et al.
Published: (2024)
by: Kwon, Jeongyeol, et al.
Published: (2024)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
A General Continuous-Time Formulation of Stochastic ADMM and Its Variants
by: Li, Chris Junchi
Published: (2024)
by: Li, Chris Junchi
Published: (2024)
Contextual Stochastic Vehicle Routing with Time Windows
by: Serrano, Breno, et al.
Published: (2024)
by: Serrano, Breno, et al.
Published: (2024)
Tame Riemannian Stochastic Approximation
by: Aspman, Johannes, et al.
Published: (2023)
by: Aspman, Johannes, et al.
Published: (2023)
Exponential Concentration in Stochastic Approximation
by: Law, Kody, et al.
Published: (2022)
by: Law, Kody, et al.
Published: (2022)
On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
by: Kong, Boao, et al.
Published: (2026)
by: Kong, Boao, et al.
Published: (2026)
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
by: Tyurin, Alexander, et al.
Published: (2024)
by: Tyurin, Alexander, et al.
Published: (2024)
Weakly Time-Coupled Approximation of Markov Decision Processes
by: Soheili, Negar, et al.
Published: (2026)
by: Soheili, Negar, et al.
Published: (2026)
Similar Items
-
Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
by: Han, Yuze, et al.
Published: (2024) -
Convergence Rate in Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence
by: Chen, Zixi, et al.
Published: (2025) -
Fast Nonlinear Two-Time-Scale Stochastic Approximation: Achieving $O(1/k)$ Finite-Sample Complexity
by: Doan, Thinh T.
Published: (2024) -
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
by: Haque, Shaan Ul, et al.
Published: (2023) -
$O(1/k)$ Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
by: Chandak, Siddharth
Published: (2025)