Pages that link to "Item:Q3648521"

The following pages link to Robust Stochastic Approximation Approach to Stochastic Programming (Q3648521):

Displaying 50 items.

• Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis (Q5162625) (← links)
• Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection (Q5162626) (← links)
• Solving variational inequalities with Stochastic Mirror-Prox algorithm (Q5168840) (← links)
• Subsampling Algorithms for Semidefinite Programming (Q5168846) (← links)
• (Q5168862) (← links)
• Multidimensional stochastic approximation (Q5176915) (← links)
• Faster Randomized Block Kaczmarz Algorithms (Q5203967) (← links)
• Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures (Q5219554) (← links)
• Incremental Constraint Projection Methods for Monotone Stochastic Variational Inequalities (Q5219716) (← links)
• Probabilistic Bisection Converges Almost as Quickly as Stochastic Approximation (Q5219733) (← links)
• Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems (Q5231692) (← links)
• Projected Stochastic Gradients for Convex Constrained Problems in Hilbert Spaces (Q5231699) (← links)
• Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity (Q5233106) (← links)
• Convergence Rate of Incremental Gradient and Incremental Newton Methods (Q5237308) (← links)
• A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization (Q5244401) (← links)
• On Solving Large-Scale Polynomial Convex Problems by Randomized First-Order Algorithms (Q5252231) (← links)
• Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning (Q5254990) (← links)
• Online Learning with (Multiple) Kernels: A Review (Q5327183) (← links)
• A STOCHASTIC APPROXIMATION ALGORITHM FOR STOCHASTIC SEMIDEFINITE PROGRAMMING (Q5358088) (← links)
• Importance sampling in signal processing applications (Q5358731) (← links)
• Optimal Affine-Invariant Smooth Minimization Algorithms (Q5376450) (← links)
• Two stochastic optimization algorithms for convex optimization with fixed point constraints (Q5379458) (← links)
• Online Pairwise Learning Algorithms (Q5380417) (← links)
• Privacy Aware Learning (Q5501941) (← links)
• Extragradient Method with Variance Reduction for Stochastic Variational Inequalities (Q5737725) (← links)
• Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization (Q5737735) (← links)
• Technical Note—Nonparametric Data-Driven Algorithms for Multiproduct Inventory Systems with Censored Demand (Q5740215) (← links)
• An Empirical Interpolation and Model-Variance Reduction Method for Computing Statistical Outputs of Parametrized Stochastic Partial Differential Equations (Q5741177) (← links)
• Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms (Q5743489) (← links)
• An acceleration procedure for optimal first-order methods (Q5746718) (← links)
• On the Convergence of Mirror Descent beyond Stochastic Convex Programming (Q5853716) (← links)
• Asymptotic Results of Stochastic Decomposition for Two-Stage Stochastic Quadratic Programming (Q5853721) (← links)
• On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional Constraints (Q5860603) (← links)
• Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems (Q5863523) (← links)
• Asymptotic Properties of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization (Q5868947) (← links)
• Bregman Finito/MISO for Nonconvex Regularized Finite Sum Minimization without Lipschitz Gradient Continuity (Q5869813) (← links)
• Smoothed Variable Sample-Size Accelerated Proximal Methods for Nonsmooth Stochastic Convex Programs (Q5870771) (← links)
• Stochastic distributed learning with gradient quantization and double-variance reduction (Q5882226) (← links)
• Block coordinate type methods for optimization and learning (Q5889894) (← links)
• Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization (Q5962719) (← links)
• Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm (Q5962728) (← links)
• Scalable estimation strategies based on stochastic approximations: classical results and new insights (Q5963780) (← links)
• Discussion on: ``Why is resorting to fate wise? A critical look at randomized algorithms in systems and control'' (Q5966128) (← links)
• Subgradient ellipsoid method for nonsmooth convex problems (Q6038646) (← links)
• Probability maximization via Minkowski functionals: convex representations and tractable resolution (Q6038654) (← links)
• An adaptive stochastic sequential quadratic programming with differentiable exact augmented Lagrangians (Q6038658) (← links)
• Unifying mirror descent and dual averaging (Q6038659) (← links)
• Semi-discrete optimal transport: hardness, regularization and numerical solution (Q6038666) (← links)
• Robust optimization of control parameters for WEC arrays using stochastic methods (Q6048456) (← links)
• Privacy-preserving federated learning on lattice quantization (Q6052296) (← links)