The following pages link to (Q3997575):
Displaying 47 items.
- Uncertainty Quantification for Stochastic Approximation Limits Using Chaos Expansion (Q5119639) (← links)
- Convergence of Markovian stochastic approximation for Markov random fields with hidden variables (Q5133905) (← links)
- Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis (Q5143323) (← links)
- Full Gradient DQN Reinforcement Learning: A Provably Convergent Scheme (Q5153609) (← links)
- Adaptive Learning Algorithm Convergence in Passive and Reactive Environments (Q5157257) (← links)
- (Q5158544) (← links)
- (Q5168862) (← links)
- Two Time-Scale Stochastic Approximation with Controlled Markov Noise and Off-Policy Temporal-Difference Learning (Q5219302) (← links)
- Convergence Rates and Decoupling in Linear Stochastic Approximation Algorithms (Q5254881) (← links)
- Principal Subspace Flows Via Mechanical Systems on Grassmann Manifolds (Q5436778) (← links)
- An Empirical Interpolation and Model-Variance Reduction Method for Computing Statistical Outputs of Parametrized Stochastic Partial Differential Equations (Q5741177) (← links)
- Asymptotic analysis of temporal-difference learning algorithms with constant step-sizes (Q5898263) (← links)
- Stochastic approximation (Q5907083) (← links)
- Asymptotic analysis of temporal-difference learning algorithms with constant step-sizes (Q5920615) (← links)
- Pole assignment for stochastic systems with unknown coefficients (Q5926408) (← links)
- Managing interprocessor delays in distributed recursive algorithms (Q5955771) (← links)
- The actor-critic algorithm as multi-time-scale stochastic approximation. (Q5955801) (← links)
- Stochastic approximation algorithms: overview and recent trends. (Q5955825) (← links)
- A sensitivity formula for risk-sensitive cost and the actor-critic algorithm (Q5958425) (← links)
- A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters (Q6047657) (← links)
- A strong convergence rate of the averaging principle for two-time-scale forward-backward stochastic differential equations (Q6071185) (← links)
- Technical note: <scp>Finite‐time</scp> regret analysis of <scp>Kiefer‐Wolfowitz</scp> stochastic approximation algorithm and nonparametric <scp>multi‐product</scp> dynamic pricing with unknown demand (Q6072149) (← links)
- Convergence of stochastic approximation via martingale and converse Lyapunov methods (Q6097904) (← links)
- Two-step estimation in linear regressions with adaptive learning (Q6101704) (← links)
- Stochastic approximation with discontinuous dynamics, differential inclusions, and applications (Q6103982) (← links)
- Estimation and inference in adaptive learning models with slowly decreasing gains (Q6134627) (← links)
- Limits of Pólya urns with innovations (Q6136796) (← links)
- A model for data transmission and its optimization (Q6139076) (← links)
- Unbiased Estimation Using Underdamped Langevin Dynamics (Q6141730) (← links)
- AI-driven liquidity provision in OTC financial markets (Q6158383) (← links)
- Convergence of the Kiefer–Wolfowitz algorithm in the presence of discontinuities (Q6159389) (← links)
- Nonsmooth optimization by Lie bracket approximations into random directions (Q6161345) (← links)
- Stochastic approximation procedures for Lévy-driven SDEs (Q6161557) (← links)
- On Unbiased Estimation for Discretized Models (Q6164172) (← links)
- Central limit theorems for stochastic gradient descent with averaging for stable manifolds (Q6164916) (← links)
- A strong averaging principle rate for two-time-scale coupled forward-backward stochastic differential equations driven by fractional Brownian motion (Q6166345) (← links)
- First-order methods for convex optimization (Q6169988) (← links)
- Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization (Q6172923) (← links)
- Large deviations for small noise diffusions over long time (Q6180755) (← links)
- High‐dimensional limit theorems for SGD: Effective dynamics and critical scaling (Q6182180) (← links)
- Persistently trained, diffusion-assisted energy-based models (Q6548884) (← links)
- Convergence guarantees for forward gradient descent in the linear regression model (Q6592792) (← links)
- Estimation of systemic shortfall risk measure using stochastic algorithms (Q6606846) (← links)
- Convergence of stochastic approximation via martingale and converse Lyapunov methods (Q6645573) (← links)
- Convergence rates for stochastic approximation: biased noise with unbounded variance, and applications (Q6655795) (← links)
- Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes (Q6657800) (← links)
- Stochastic gradient descent in continuous time for drift identification in multiscale diffusions (Q6667317) (← links)
