Pages that link to "Item:Q2196224"

The following pages link to Bridging the gap between constant step size stochastic gradient descent and Markov chains (Q2196224):

Displaying 25 items.

• Analysis of stochastic gradient descent in continuous time (Q2058762) (← links)
• A regularized stochastic subgradient projection method for an optimal control problem in a stochastic partial differential equation (Q2080615) (← links)
• Dimension independent excess risk by stochastic gradient descent (Q2084455) (← links)
• On sampling from a log-concave density using kinetic Langevin diffusions (Q2174987) (← links)
• (Q4637063) (← links)
• (Q4967840) (← links)
• (Q4998888) (← links)
• (Q4999045) (← links)
• Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence (Q5018894) (← links)
• On the Effectiveness of Richardson Extrapolation in Data Science (Q5018900) (← links)
• Hausdorff dimension, heavy tails, and generalization in neural networks* (Q5020059) (← links)
• Some Limit Properties of Markov Chains Induced by Recursive Stochastic Algorithms (Q5037552) (← links)
• Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates (Q5072589) (← links)
• An iteratively regularized stochastic gradient method for estimating a random parameter in a stochastic PDE. A variational inequality approach (Q5089997) (← links)
• A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares) (Q5136291) (← links)
• Bayesian Inverse Problems Are Usually Well-Posed (Q6115454) (← links)
• Stochastic elliptic inverse problems. Solvability, convergence rates, discretization, and applications (Q6137266) (← links)
• A new regularized stochastic approximation framework for stochastic inverse problems (Q6158281) (← links)
• Nonexpansive Markov operators and random function iterations for stochastic fixed point problems (Q6178237) (← links)
• High‐dimensional limit theorems for SGD: Effective dynamics and critical scaling (Q6182180) (← links)
• Estimation and inference by stochastic optimization (Q6193080) (← links)
• Stochastic differential equation approximations of generative adversarial network training and its long-run behavior (Q6500023) (← links)
• A large-sample theory for infinitesimal gradient boosting (Q6565306) (← links)
• Probability and moment inequalities for additive functionals of geometrically ergodic Markov chains (Q6592137) (← links)
• A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques (Q6620576) (← links)