Pages that link to "Item:Q4509729"

The following pages link to Gradient Convergence in Gradient methods with Errors (Q4509729):

Displaying 42 items.

• The Malliavin gradient method for the calibration of stochastic dynamical models (Q2493710) (← links)
• Global optimization issues in deep network regression: an overview (Q2633536) (← links)
• Two-timescale stochastic gradient descent in continuous time with applications to joint online parameter estimation and optimal sensor placement (Q2692526) (← links)
• Adaptive error control during gradient search for an elliptic optimization problem (Q2844775) (← links)
• New combinatorial direction stochastic approximation algorithms (Q2867404) (← links)
• Error Bounds for Least Squares Gradient Estimates (Q2998027) (← links)
• On perturbed steepest descent methods with inexact line search for bilevel convex optimization (Q3112499) (← links)
• Descent direction method with line search for unconstrained optimization in noisy environment (Q3458837) (← links)
• Errors of gradient extrema of a strictly convex function of discrete argument (Q4284965) (← links)
• Stochastic Gradient Descent in Continuous Time (Q4607057) (← links)
• String-averaging incremental stochastic subgradient algorithms (Q4631774) (← links)
• (Q5019878) (← links)
• Distributed Bregman-Distance Algorithms for Min-Max Optimization (Q5023087) (← links)
• An iteratively regularized stochastic gradient method for estimating a random parameter in a stochastic PDE. A variational inequality approach (Q5089997) (← links)
• On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming (Q5219732) (← links)
• Projected Stochastic Gradients for Convex Constrained Problems in Hilbert Spaces (Q5231699) (← links)
• Convergence Rate of Incremental Gradient and Incremental Newton Methods (Q5237308) (← links)
• Timescale Separation in Recurrent Neural Networks (Q5380251) (← links)
• Bregman Finito/MISO for Nonconvex Regularized Finite Sum Minimization without Lipschitz Gradient Continuity (Q5869813) (← links)
• Stochastic Difference-of-Convex-Functions Algorithms for Nonconvex Programming (Q5869814) (← links)
• Stochastic approximation algorithms: overview and recent trends. (Q5955825) (← links)
• Zeroth-order optimization with orthogonal random directions (Q6038668) (← links)
• Convergence analysis of AdaBound with relaxed bound functions for non-convex optimization (Q6055172) (← links)
• Stochastic momentum methods for non-convex learning without bounded assumptions (Q6057975) (← links)
• An online gradient-based parameter identification algorithm for the neuro-fuzzy systems (Q6081511) (← links)
• Online parameter estimation for the McKean-Vlasov stochastic differential equation (Q6115259) (← links)
• Convergence analysis for sigma-pi-sigma neural network based on some relaxed conditions (Q6149503) (← links)
• On stochastic roundoff errors in gradient descent with low-precision computation (Q6150643) (← links)
• A Convergence Study of SGD-Type Methods for Stochastic Optimization (Q6151338) (← links)
• A new regularized stochastic approximation framework for stochastic inverse problems (Q6158281) (← links)
• Convergence of Random Reshuffling under the Kurdyka–Łojasiewicz Inequality (Q6161313) (← links)
• Convergence of gradient algorithms for nonconvex \(C^{1+ \alpha}\) cost functions (Q6167107) (← links)
• Continuous‐time stochastic gradient descent for optimizing over the stationary distribution of stochastic differential equations (Q6196292) (← links)
• GANs training: A game and stochastic control approach (Q6196295) (← links)
• SPIRAL: a superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization (Q6498409) (← links)
• Fast and correct gradient-based optimisation for probabilistic programming via smoothing (Q6535252) (← links)
• Subsampled first-order optimization methods with applications in imaging (Q6606441) (← links)
• Tuning parameters of deep neural network training algorithms pays off: a computational study (Q6635854) (← links)
• Sequential quadratic optimization for stochastic optimization with deterministic nonlinear inequality and equality constraints (Q6644844) (← 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)
• Stochastic gradient descent in continuous time for drift identification in multiscale diffusions (Q6667317) (← links)