Pages that link to "Item:Q3648521"

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

Displaying 50 items.

• An optimal randomized incremental gradient method (Q1785198) (← links)
• Robust sample average approximation (Q1785199) (← links)
• On sample average approximation algorithms for determining the optimal importance sampling parameters in pricing financial derivatives on Lévy processes (Q1785463) (← links)
• The sample average approximation method applied to stochastic routing problems: a computational study (Q1866135) (← links)
• Tractable approximation to robust nonlinear production frontier problem (Q1925472) (← links)
• A new hybrid stochastic approximation algorithm (Q1941202) (← links)
• A quasi-Monte-Carlo-based feasible sequential system of linear equations method for stochastic programs with recourse (Q1992358) (← links)
• Aggregate subgradient method for nonsmooth DC optimization (Q1996741) (← links)
• Towards easier and faster sequence labeling for natural language processing: a search-based probabilistic online learning framework (SAPO) (Q2004713) (← links)
• Surrogate-based robust design for a non-smooth radiation source detection problem (Q2004893) (← links)
• A primal sub-gradient method for structured classification with the averaged sum loss (Q2018420) (← links)
• Convergence of stochastic proximal gradient algorithm (Q2019902) (← links)
• Point process estimation with Mirror Prox algorithms (Q2019904) (← links)
• Distributed stochastic gradient tracking methods (Q2020611) (← links)
• Dynamic stochastic approximation for multi-stage stochastic optimization (Q2020613) (← links)
• Inexact stochastic mirror descent for two-stage nonlinear stochastic programs (Q2020614) (← links)
• Saddle point approximation approaches for two-stage robust optimization problems (Q2022185) (← links)
• Stochastic proximal gradient methods for nonconvex problems in Hilbert spaces (Q2028468) (← links)
• Tutorial on risk neutral, distributionally robust and risk averse multistage stochastic programming (Q2028833) (← links)
• General convergence analysis of stochastic first-order methods for composite optimization (Q2032020) (← links)
• Gradient convergence of deep learning-based numerical methods for BSDEs (Q2044106) (← links)
• Fastest rates for stochastic mirror descent methods (Q2044496) (← links)
• Minibatch stochastic subgradient-based projection algorithms for feasibility problems with convex inequalities (Q2044573) (← links)
• Inexact stochastic subgradient projection method for stochastic equilibrium problems with nonmonotone bifunctions: application to expected risk minimization in machine learning (Q2045021) (← links)
• On the analysis of variance-reduced and randomized projection variants of single projection schemes for monotone stochastic variational inequality problems (Q2045192) (← links)
• A stochastic primal-dual method for optimization with conditional value at risk constraints (Q2046691) (← links)
• Stochastic proximal splitting algorithm for composite minimization (Q2047212) (← links)
• Infinite-dimensional gradient-based descent for alpha-divergence minimisation (Q2054493) (← links)
• Unified binary generative adversarial network for image retrieval and compression (Q2056141) (← links)
• Stochastic generalized gradient methods for training nonconvex nonsmooth neural networks (Q2058689) (← links)
• Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation (Q2058738) (← links)
• Analysis of stochastic gradient descent in continuous time (Q2058762) (← links)
• Consistent online Gaussian process regression without the sample complexity bottleneck (Q2058904) (← links)
• A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs (Q2063194) (← links)
• Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence (Q2073208) (← links)
• Distributionally robust optimization. A review on theory and applications (Q2074636) (← links)
• Stochastic relaxed inertial forward-backward-forward splitting for monotone inclusions in Hilbert spaces (Q2082546) (← links)
• A PAC algorithm in relative precision for bandit problem with costly sampling (Q2084297) (← links)
• Stopping criteria for, and strong convergence of, stochastic gradient descent on Bottou-Curtis-Nocedal functions (Q2089787) (← links)
• A study of data-driven distributionally robust optimization with incomplete joint data under finite support (Q2098046) (← links)
• A stochastic Nesterov's smoothing accelerated method for general nonsmooth constrained stochastic composite convex optimization (Q2103421) (← links)
• A stochastic gradient algorithm with momentum terms for optimal control problems governed by a convection-diffusion equation with random diffusivity (Q2104094) (← links)
• On stochastic accelerated gradient with convergence rate (Q2111814) (← links)
• Two-stage linear decision rules for multi-stage stochastic programming (Q2118081) (← links)
• A hybrid stochastic optimization framework for composite nonconvex optimization (Q2118109) (← links)
• Stochastic gradient descent for semilinear elliptic equations with uncertainties (Q2127008) (← links)
• Understanding generalization error of SGD in nonconvex optimization (Q2127232) (← links)
• Sample average approximation for stochastic nonconvex mixed integer nonlinear programming via outer-approximation (Q2129194) (← links)
• Parallel random block-coordinate forward-backward algorithm: a unified convergence analysis (Q2133415) (← links)
• A primal-dual algorithm for risk minimization (Q2133418) (← links)