Pages that link to "Item:Q3978271"

The following pages link to Recursive Stochastic Algorithms for Global Optimization in $\mathbb{R}^d $ (Q3978271):

Displaying 50 items.

• Multiscale Q-learning with linear function approximation (Q312650) (← links)
• Simulated annealing simulated (Q678432) (← links)
• Convergence analysis of a global optimization algorithm using stochastic differential equations (Q842717) (← links)
• Linearly constrained global optimization and stochastic differential equations (Q857812) (← links)
• Global optimization using diffusion perturbations with large noise intensity (Q861400) (← links)
• A strong approximation theorem for stochastic recursive algorithms (Q1289391) (← links)
• Weak convergence rates for stochastic approximation with application to multiple targets and simulated annealing (Q1296615) (← links)
• Recursive identification in continuous-time stochastic processes (Q1316601) (← links)
• Global optimization by random perturbation of the gradient method with a fixed parameter (Q1337130) (← links)
• Stochastic approximation of global minimum points (Q1338378) (← links)
• Convergence of the simulated annealing algorithm for continuous global optimization (Q1573995) (← links)
• Almost surely convergent global optimziation algorithm using noise-corrupted observations (Q1579659) (← links)
• Stability of annealing schemes and related processes (Q1589565) (← links)
• Distributed stochastic algorithm for global optimization in networked system (Q1626540) (← links)
• Stochastic optimization of forward recursive functions (Q1826762) (← links)
• A stochastic optimization method for the evaluation of minima up to \(\varepsilon\) (Q1865021) (← links)
• An adaptive simulated annealing algorithm. (Q1888770) (← links)
• Simulated annealing algorithms for continuous global optimization: Convergence conditions (Q1973485) (← links)
• Simultaneous small noise limit for singularly perturbed slow-fast coupled diffusions (Q2041038) (← links)
• Stochastic gradient Hamiltonian Monte Carlo for non-convex learning (Q2137760) (← links)
• Non-asymptotic guarantees for sampling by stochastic gradient descent (Q2290072) (← links)
• Stochastic global maximum principle for optimization with recursive utilities (Q2296089) (← links)
• Improving simulated annealing through derandomization (Q2397439) (← links)
• Convergence rates of Gibbs measures with degenerate minimum (Q2676926) (← links)
• Optimising portfolio diversification and dimensionality (Q2679246) (← links)
• APPROACHES TO ADAPTIVE STOCHASTIC SEARCH BASED ON THE NONEXTENSIVE q-DISTRIBUTION (Q3598855) (← links)
• Convergence of a global stochastic optimization algorithm with partial step size restarting (Q4507953) (← links)
• Numerical optimization and quasiconvexity (Q4835505) (← links)
• (Q4999096) (← links)
• Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence (Q5018894) (← links)
• One-dimensional system arising in stochastic gradient descent (Q5022277) (← links)
• Some Limit Properties of Markov Chains Induced by Recursive Stochastic Algorithms (Q5037552) (← links)
• Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Nonconvex Stochastic Optimization: Nonasymptotic Performance Bounds and Momentum-Based Acceleration (Q5058053) (← links)
• State-Dependent Temperature Control for Langevin Diffusions (Q5080490) (← links)
• A Concentration Bound for Stochastic Approximation via Alekseev’s Formula (Q5113889) (← links)
• Second-Order Guarantees of Distributed Gradient Algorithms (Q5131964) (← links)
• (Q5159457) (← links)
• Multiscale Stochastic Approximation for Parametric Optimization of Hidden Markov Models (Q5488556) (← links)
• Embedding Learning (Q5881086) (← links)
• Stochastic approximation (Q5907083) (← links)
• Approximation of an analog diffusion network with applications to image estimation (Q5925728) (← links)
• Managing interprocessor delays in distributed recursive algorithms (Q5955771) (← links)
• Stochastic approximation algorithms: overview and recent trends. (Q5955825) (← links)
• Unadjusted Langevin algorithm with multiplicative noise: total variation and Wasserstein bounds (Q6103981) (← links)
• On the Generalized Langevin Equation for Simulated Annealing (Q6109158) (← links)
• Swarm gradient dynamics for global optimization: the mean-field limit case (Q6126662) (← links)
• Delay-induced homoclinic bifurcations in modified gradient bistable systems and their relevance to optimization (Q6556964) (← links)
• Optimization with delay-induced bifurcations (Q6562257) (← links)
• Adaptive state-dependent diffusion for derivative-free optimization (Q6575305) (← links)
• Swing contract pricing: with and without neural networks (Q6581630) (← links)