Pages that link to "Item:Q3648521"

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

Displaying 50 items.

• Linear convergence of first order methods for non-strongly convex optimization (Q2414900) (← links)
• Primal-dual mirror descent method for constraint stochastic optimization problems (Q2416753) (← links)
• Accelerated randomized mirror descent algorithms for composite non-strongly convex optimization (Q2420797) (← links)
• On the convergence of asynchronous parallel iteration with unbounded delays (Q2422607) (← links)
• Randomized first order algorithms with applications to \(\ell _{1}\)-minimization (Q2434980) (← links)
• A nonmonotone approximate sequence algorithm for unconstrained nonlinear optimization (Q2436686) (← links)
• The asymptotics of ranking algorithms (Q2438754) (← links)
• Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization (Q2515032) (← links)
• Asymptotic optimality in stochastic optimization (Q2656586) (← links)
• When can we improve on sample average approximation for stochastic optimization? (Q2661521) (← links)
• Differentially private SGD with non-smooth losses (Q2667048) (← links)
• Two fast variance-reduced proximal gradient algorithms for SMVIPs -- stochastic mixed variational inequality problems with suitable applications to stochastic network games and traffic assignment problems (Q2668043) (← links)
• Risk bounds when learning infinitely many response functions by ordinary linear regression (Q2686603) (← links)
• Policy mirror descent for reinforcement learning: linear convergence, new sampling complexity, and generalized problem classes (Q2687069) (← links)
• Regularized sample average approximation for high-dimensional stochastic optimization under low-rankness (Q2687436) (← links)
• Sample average approximations of strongly convex stochastic programs in Hilbert spaces (Q2688927) (← links)
• Complexity guarantees for an implicit smoothing-enabled method for stochastic MPECs (Q2693641) (← links)
• Accelerated stochastic variance reduction for a class of convex optimization problems (Q2696969) (← links)
• A stochastic inertial forward–backward splitting algorithm for multivariate monotone inclusions (Q2810123) (← links)
• A dynamic programming approach for a class of robust optimization problems (Q2817842) (← links)
• Ergodic convergence of a stochastic proximal point algorithm (Q2828340) (← links)
• Coordinate descent with arbitrary sampling I: algorithms and complexity^† (Q2829565) (← links)
• A family of subgradient-based methods for convex optimization problems in a unifying framework (Q2829570) (← links)
• On the solution of stochastic optimization and variational problems in imperfect information regimes (Q2832894) (← links)
• Adaptive Sampling for Incremental Optimization Using Stochastic Gradient Descent (Q2835640) (← links)
• Optimal budget allocation for sample average approximation (Q2846430) (← links)
• A non-monotonic method for large-scale non-negative least squares (Q2867422) (← links)
• Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization (Q2921184) (← links)
• A smoothing stochastic gradient method for composite optimization (Q2926083) (← links)
• Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization (Q2945126) (← links)
• Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties (Q2954387) (← links)
• Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization (Q2954396) (← links)
• Mitigating Uncertainty via Compromise Decisions in Two-Stage Stochastic Linear Programming: Variance Reduction (Q2957466) (← links)
• Penalty methods with stochastic approximation for stochastic nonlinear programming (Q2970100) (← links)
• Some multivariate risk indicators: Minimization by using a Kiefer–Wolfowitz approach to the mirror stochastic algorithm (Q3224136) (← links)
• How Effectively Train Large-Scale Machine Learning Models? (Q3299229) (← links)
• A Robust Optimization Perspective on Stochastic Programming (Q3392134) (← links)
• Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints (Q3465237) (← links)
• Adaptive random search for continuous simulation optimization (Q3588809) (← links)
• Robust Solutions in Stochastic Linear Programming (Q3983498) (← links)
• Robustness analysis for stochastic approximation algorithms (Q4204968) (← links)
• Monte Carlo sampling approach to stochastic programming (Q4452116) (← links)
• Optimal order placement in limit order markets (Q4555056) (← links)
• RSG: Beating Subgradient Method without Smoothness and Strong Convexity (Q4558142) (← links)
• (Q4558475) (← links)
• (Q4558495) (← links)
• Nonasymptotic convergence of stochastic proximal point algorithms for constrained convex optimization (Q4558525) (← links)
• Stochastic Methods for Composite and Weakly Convex Optimization Problems (Q4561227) (← links)
• A Level-Set Method for Convex Optimization with a Feasible Solution Path (Q4562247) (← links)
• Distributed Stochastic Approximation with Local Projections (Q4562250) (← links)