Imagen de Portada

Markov Chain Variance Estimation: A Stochastic Approximation Approach

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Agrawal, Shubhada, A., Prashanth L., Maguluri, Siva Theja
Formato:	Preprint
Publicado:	2024
Materias:	Statistics Theory Probability Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
por: Wang, Zedong, et al.
Publicado: (2026)

An Analysis of Elo Rating Systems via Markov Chains
por: Olesker-Taylor, Sam, et al.
Publicado: (2024)

Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
por: Agrawal, Shubhada, et al.
Publicado: (2025)

Cover meets Robbins while Betting on Bounded Data: $\ln n$ Regret and Almost Sure $\ln\ln n$ Regret
por: Agrawal, Shubhada, et al.
Publicado: (2026)

On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
por: Agrawal, Shubhada, et al.
Publicado: (2025)

Complexity of Markov Chain Monte Carlo for Generalized Linear Models
por: Chak, Martin, et al.
Publicado: (2025)

Federated Stochastic Approximation under Markov Noise and Heterogeneity: Applications in Reinforcement Learning
por: Khodadadian, Sajad, et al.
Publicado: (2022)

Almost sure null bankruptcy of testing-by-betting strategies
por: Wang, Hongjian, et al.
Publicado: (2026)

Sharp Concentration Inequalities: Phase Transition and Mixing of Orlicz Tails with Variance
por: Shen, Yinan, et al.
Publicado: (2026)

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

Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing
por: Zhang, Yihan, et al.
Publicado: (2023)

Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
por: Shi, Zhaoyang, et al.
Publicado: (2024)

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

A Complete Decomposition of Stochastic Differential Equations
por: Duffield, Samuel
Publicado: (2026)

Optimal Estimation in Orthogonally Invariant Generalized Linear Models: Spectral Initialization and Approximate Message Passing
por: Zhang, Yihan, et al.
Publicado: (2026)

Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
por: Shi, Zhaoyang, et al.
Publicado: (2024)

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
por: Balasubramanian, Krishnakumar, et al.
Publicado: (2025)

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
por: Miranda, Charles, et al.
Publicado: (2023)

Higher-Order Approximations of Sojourn Times in M/G/1 Queues via Stein's Method
por: Chatterjee, Bihan, et al.
Publicado: (2026)

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks
por: Rangriz, Parsa
Publicado: (2025)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities
por: Carpentier, Alexandra, et al.
Publicado: (2025)

Partial recovery and weak consistency in the non-uniform hypergraph Stochastic Block Model
por: Dumitriu, Ioana, et al.
Publicado: (2021)

Optimal and exact recovery on general non-uniform Hypergraph Stochastic Block Model
por: Dumitriu, Ioana, et al.
Publicado: (2023)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities (II)
por: Carpentier, Alexandra, et al.
Publicado: (2025)

Tail Bounds for Queues with Abandonment: Constant, Moderate, Large Deviations, and Efficient Concentration
por: Wang, Zedong, et al.
Publicado: (2026)

On Universality of Non-Separable Approximate Message Passing Algorithms
por: Lovig, Max, et al.
Publicado: (2025)

Probabilistic Conformal Prediction with Approximate Conditional Validity
por: Plassier, Vincent, et al.
Publicado: (2024)

Optimistic Estimation of Convergence in Markov Chains with the Average-Mixing Time
por: Wolfer, Geoffrey, et al.
Publicado: (2024)

Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
por: Morisset, Lucas, et al.
Publicado: (2025)

Diffusion Models with Heavy-Tailed Targets: Score Estimation and Sampling Guarantees
por: Yu, Yifeng, et al.
Publicado: (2026)

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

Revenue Maximization Under Sequential Price Competition Via The Estimation Of s-Concave Demand Functions
por: Bracale, Daniele, et al.
Publicado: (2025)

Adaptive Estimation of Multivariate Piecewise Polynomials and Bounded Variation Functions by Optimal Decision Trees
por: Chatterjee, Sabyasachi, et al.
Publicado: (2019)

A Heavy Traffic Theory of Matching Queues
por: Varma, Sushil Mahavir, et al.
Publicado: (2021)

Equilibrium Distribution for t-Distributed Stochastic Neighbor Embedding with Generalized Kernels
por: Gu, Yi
Publicado: (2025)

Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
por: Dudeja, Rishabh, et al.
Publicado: (2024)

Estimating stationary mass, frequency by frequency
por: Nakul, Milind, et al.
Publicado: (2025)

Information-Theoretic Limits and Strong Consistency on Binary Non-uniform Hypergraph Stochastic Block Models
por: Wang, Hai-Xiao
Publicado: (2023)