Imagen de Portada

A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Chen, Zaiwei, Zhang, Sheng, Zhang, Zhe, Haque, Shaan Ul, Maguluri, Siva Theja
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Optimization and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose Theorem
por: Haque, Shaan Ul, et al.
Publicado: (2024)

Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
por: Haque, Shaan Ul, et al.
Publicado: (2023)

Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework
por: Chen, Zaiwei, et al.
Publicado: (2026)

Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
por: Chen, Zaiwei, et al.
Publicado: (2023)

Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise
por: Agrawal, Shubhada, et al.
Publicado: (2026)

How Accurately Can a Gaussian Approximate Stochastic Approximation Iterates?
por: Haque, Shaan Ul, et al.
Publicado: (2026)

Performance of NPG in Countable State-Space Average-Cost RL
por: Murthy, Yashaswini, et al.
Publicado: (2024)

Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise
por: Chandak, Siddharth, et al.
Publicado: (2025)

Electric Vehicle Fleet and Charging Infrastructure Planning
por: Varma, Sushil Mahavir, et al.
Publicado: (2023)

Stochastic Approximation for Nonlinear Discrete Stochastic Control: Finite-Sample Bounds
por: Nguyen, Hoang Huy, et al.
Publicado: (2023)

Almost Sure Convergence of Stochastic Approximation: An Interplay of Noise and Step Size
por: Nguyen, Quang Dinh Thien, et al.
Publicado: (2026)

Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework
por: Nanda, Phalguni, et al.
Publicado: (2026)

Dynamic Pricing and Matching for Two-Sided Queues
por: Varma, Sushil Mahavir, et al.
Publicado: (2019)

Optimal Pricing in Multi Server Systems
por: S, Ashok Krishnan K., et al.
Publicado: (2021)

Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
por: Kong, Deyi, et al.
Publicado: (2026)

A Minimal-Assumption Analysis of Q-Learning with Time-Varying Policies
por: Nanda, Phalguni, et al.
Publicado: (2025)

Achieving $ε^{-2}$ Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions
por: Hamza, Ishaq, et al.
Publicado: (2026)

Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
por: Pan, Xiaokang, et al.
Publicado: (2024)

Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
por: Vaidyan, Kevin Kurian Thomas, et al.
Publicado: (2026)

Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints
por: Ablin, Pierre, et al.
Publicado: (2023)

Single-Loop Deterministic and Stochastic Interior-Point Algorithms for Nonlinearly Constrained Optimization
por: Curtis, Frank E., et al.
Publicado: (2024)

Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems
por: Siriya, Seth, et al.
Publicado: (2024)

Non-Asymptotic Optimization and Generalization Bounds for Stochastic Gauss-Newton in Overparameterized Models
por: Cayci, Semih
Publicado: (2025)

Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
por: Keane, Ronan
Publicado: (2024)

Lyapunov Stability of Stochastic Vector Optimization: Theory and Numerical Implementation
por: Santos, Thiago, et al.
Publicado: (2026)

Non-Asymptotic Global Convergence of PPO-Clip
por: Liu, Yin, et al.
Publicado: (2025)

Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
por: Grazzi, Riccardo, et al.
Publicado: (2024)

Linearly Convergent Algorithms for Nonsmooth Problems with Unknown Smooth Pieces
por: Zhang, Zhe, et al.
Publicado: (2025)

$ψ$DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
por: Ziu, Klea, et al.
Publicado: (2024)

Stochastic Compositional Optimization with Compositional Constraints
por: Yang, Shuoguang, et al.
Publicado: (2022)

The Stochastic Conjugate Subgradient Algorithm For Kernel Support Vector Machines
por: Zhang, Di, et al.
Publicado: (2024)

A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm
por: Leong, Oscar, et al.
Publicado: (2025)

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
por: Liu, Zijian, et al.
Publicado: (2023)

Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
por: Long, Kehan, et al.
Publicado: (2025)

Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise
por: Blaser, Ethan, et al.
Publicado: (2024)

Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity
por: Li, Jin, et al.
Publicado: (2021)

Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
por: Tang, Xun, et al.
Publicado: (2024)

Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
por: Dang, Thanh, et al.
Publicado: (2025)

Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
por: Huang, Ruichuan, et al.
Publicado: (2025)

Edge of Stochastic Stability: Revisiting the Edge of Stability for SGD
por: Andreyev, Arseniy, et al.
Publicado: (2024)