Revisiting Stochastic Approximation and Stochastic Gradient Descent
Fuente:
arXiv
Saved in:
| Main Authors: | Karandikar, Rajeeva Laxman, Rao, Bhamidi Visweswara, Vidyasagar, Mathukumalli |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications
by: Karandikar, Rajeeva L., et al.
Published: (2023)
by: Karandikar, Rajeeva L., et al.
Published: (2023)
Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning
by: Karandikar, Rajeeva L., et al.
Published: (2021)
by: Karandikar, Rajeeva L., et al.
Published: (2021)
Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent
by: Sheshukova, Marina, et al.
Published: (2025)
by: Sheshukova, Marina, et al.
Published: (2025)
On the Rate of Gaussian Approximation for Linear Regression Problems
by: Khusainov, Marat, et al.
Published: (2025)
by: Khusainov, Marat, et al.
Published: (2025)
Statistical inference for Linear Stochastic Approximation with Markovian Noise
by: Samsonov, Sergey, et al.
Published: (2025)
by: Samsonov, Sergey, et al.
Published: (2025)
Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation
by: Butyrin, Bogdan, et al.
Published: (2025)
by: Butyrin, Bogdan, et al.
Published: (2025)
Stochastic Modified Flows for Riemannian Stochastic Gradient Descent
by: Gess, Benjamin, et al.
Published: (2024)
by: Gess, Benjamin, et al.
Published: (2024)
Gaussian Approximation for Two-Timescale Linear Stochastic Approximation
by: Butyrin, Bogdan, et al.
Published: (2025)
by: Butyrin, Bogdan, et al.
Published: (2025)
Adaptive Stochastic Gradient Descents on Manifolds with an Application on Weighted Low-Rank Approximation
by: Yang, Peiqi, et al.
Published: (2025)
by: Yang, Peiqi, et al.
Published: (2025)
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
by: Samsonov, Sergey, et al.
Published: (2024)
by: Samsonov, Sergey, et al.
Published: (2024)
Sample Average Approximation for Stochastic Programming with Equality Constraints
by: Lew, Thomas, et al.
Published: (2022)
by: Lew, Thomas, et al.
Published: (2022)
Stochastic Control with Signatures
by: Bank, P., et al.
Published: (2024)
by: Bank, P., et al.
Published: (2024)
Learning to reflect: A unifying approach for data-driven stochastic control strategies
by: Christensen, Sören, et al.
Published: (2021)
by: Christensen, Sören, et al.
Published: (2021)
Convergence of Riemannian Stochastic Gradient Descents: Varying Batch Sizes And Nonstandard Batch Forming
by: Wu, Hao
Published: (2026)
by: Wu, Hao
Published: (2026)
Asynchronous Stochastic Approximation with Applications to Average-Reward Reinforcement Learning
by: Yu, Huizhen, et al.
Published: (2024)
by: Yu, Huizhen, et al.
Published: (2024)
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
by: Sheshukova, Marina, et al.
Published: (2024)
by: Sheshukova, Marina, et al.
Published: (2024)
Sample Complexity of Policy Gradient for Log-Growth Control
by: Pan, Qiuhua, et al.
Published: (2026)
by: Pan, Qiuhua, et al.
Published: (2026)
Mini-Batch Covariance, Diffusion Limits, and Oracle Complexity in Stochastic Gradient Descent: A Sampling-Design Perspective
by: Zantedeschi, Daniel, et al.
Published: (2026)
by: Zantedeschi, Daniel, et al.
Published: (2026)
Stability and Sensitivity Analysis of Relative Temporal-Difference Learning: Extended Version
by: Sakha, Masoud S., et al.
Published: (2026)
by: Sakha, Masoud S., et al.
Published: (2026)
Optimistic Training and Convergence of Q-Learning -- Extended Version
by: Mehta, Prashant, et al.
Published: (2026)
by: Mehta, Prashant, et al.
Published: (2026)
A geometric ensemble method for Bayesian inference
by: Popov, Andrey A
Published: (2025)
by: Popov, Andrey A
Published: (2025)
Optimal State Equation for the Control of a Diffusion with Two Distinct Dynamics
by: Chen, Zengjing, et al.
Published: (2024)
by: Chen, Zengjing, et al.
Published: (2024)
The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning
by: Borkar, Vivek, et al.
Published: (2021)
by: Borkar, Vivek, et al.
Published: (2021)
A Sequential Testing Problem with Signal Control
by: Campbell, Steven, et al.
Published: (2025)
by: Campbell, Steven, et al.
Published: (2025)
Gradient Flows for Regularized Stochastic Control Problems
by: Šiška, David, et al.
Published: (2020)
by: Šiška, David, et al.
Published: (2020)
Optimality of a barrier strategy in a spectrally negative Lévy model with a level-dependent intensity of bankruptcy
by: Mata, Dante, et al.
Published: (2024)
by: Mata, Dante, et al.
Published: (2024)
Markovian Foundations for Quasi-Stochastic Approximation with Applications to Extremum Seeking Control
by: Lauand, Caio Kalil, et al.
Published: (2022)
by: Lauand, Caio Kalil, et al.
Published: (2022)
A Note on Stability in Asynchronous Stochastic Approximation without Communication Delays
by: Yu, Huizhen, et al.
Published: (2023)
by: Yu, Huizhen, et al.
Published: (2023)
Stochastic Control of Drawdowns via Reinsurance under Random Inspection
by: Dudziak, Kira, et al.
Published: (2025)
by: Dudziak, Kira, et al.
Published: (2025)
Finite-Time Analysis of Projected Two-Time-Scale Stochastic Approximation
by: Bai, Yitao, et al.
Published: (2026)
by: Bai, Yitao, et al.
Published: (2026)
Approximate robust output regulation of boundary control systems
by: Humaloja, Jukka-Pekka, et al.
Published: (2017)
by: Humaloja, Jukka-Pekka, et al.
Published: (2017)
Markov approximation for controlled Hawkes Jump-Diffusions with general kernels
by: Khabou, Mahmoud, et al.
Published: (2025)
by: Khabou, Mahmoud, et al.
Published: (2025)
Convergence of Policy Iteration for Entropy-Regularized Stochastic Control Problems
by: Huang, Yu-Jui, et al.
Published: (2022)
by: Huang, Yu-Jui, et al.
Published: (2022)
A Short Survey of Averaging Techniques in Stochastic Gradient Methods
by: Lakshmanan, K.
Published: (2026)
by: Lakshmanan, K.
Published: (2026)
Convergence of the Stochastic Heavy Ball Method With Approximate Gradients and/or Block Updating
by: Tadipatri, Uday Kiran Reddy, et al.
Published: (2023)
by: Tadipatri, Uday Kiran Reddy, et al.
Published: (2023)
Signature Methods in Stochastic Portfolio Theory
by: Cuchiero, Christa, et al.
Published: (2023)
by: Cuchiero, Christa, et al.
Published: (2023)
Hautus-Type Criteria for Controllability and Stabilizability of Backward-Structured Stochastic Systems
by: Sun, Jingrui
Published: (2026)
by: Sun, Jingrui
Published: (2026)
Stochastic Optimal Control Problems for the Cost-Optimal Management of a Standalone Microgrid
by: Takam, Paul Honore, et al.
Published: (2025)
by: Takam, Paul Honore, et al.
Published: (2025)
A measure-valued HJB perspective on Bayesian optimal adaptive control
by: Cox, Alexander M. G., et al.
Published: (2025)
by: Cox, Alexander M. G., et al.
Published: (2025)
Linear-Quadratic Optimal Control for Mean-Field Stochastic Differential Equations in Infinite-Horizon with Regime Switching
by: Mei, Hongwei, et al.
Published: (2025)
by: Mei, Hongwei, et al.
Published: (2025)
Similar Items
-
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications
by: Karandikar, Rajeeva L., et al.
Published: (2023) -
Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning
by: Karandikar, Rajeeva L., et al.
Published: (2021) -
Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent
by: Sheshukova, Marina, et al.
Published: (2025) -
On the Rate of Gaussian Approximation for Linear Regression Problems
by: Khusainov, Marat, et al.
Published: (2025) -
Statistical inference for Linear Stochastic Approximation with Markovian Noise
by: Samsonov, Sergey, et al.
Published: (2025)