Pages that link to "Item:Q3648521"

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

Displaying 50 items.

• Improved variance reduction extragradient method with line search for stochastic variational inequalities (Q6064028) (← links)
• Technical note: <scp>Finite‐time</scp> regret analysis of <scp>Kiefer‐Wolfowitz</scp> stochastic approximation algorithm and nonparametric <scp>multi‐product</scp> dynamic pricing with unknown demand (Q6072149) (← links)
• Randomized Kaczmarz method with adaptive stepsizes for inconsistent linear systems (Q6076947) (← links)
• Unified analysis of stochastic gradient methods for composite convex and smooth optimization (Q6086133) (← links)
• Adaptive stochastic gradient descent for optimal control of parabolic equations with random parameters (Q6090392) (← links)
• Block Policy Mirror Descent (Q6093281) (← links)
• Parallel and distributed asynchronous adaptive stochastic gradient methods (Q6095736) (← links)
• Scaling up stochastic gradient descent for non-convex optimisation (Q6097095) (← links)
• A framework of convergence analysis of mini-batch stochastic projected gradient methods (Q6097385) (← links)
• A relaxation-based probabilistic approach for PDE-constrained optimization under uncertainty with pointwise state constraints (Q6097761) (← links)
• A stochastic variance-reduced accelerated primal-dual method for finite-sum saddle-point problems (Q6097769) (← links)
• Stochastic mirror descent method for linear ill-posed problems in Banach spaces (Q6101039) (← links)
• Variational Bayesian analysis of nonhomogeneous hidden Markov models with long and ultralong sequences (Q6104143) (← links)
• A stochastic variance reduction algorithm with Bregman distances for structured composite problems (Q6106321) (← links)
• Convergence rates of the stochastic alternating algorithm for bi-objective optimization (Q6108978) (← links)
• Stochastic composition optimization of functions without Lipschitz continuous gradient (Q6108982) (← links)
• Faster randomized block sparse Kaczmarz by averaging (Q6109882) (← links)
• Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems (Q6120842) (← links)
• Limitations of neural network training due to numerical instability of backpropagation (Q6122651) (← links)
• Optimal analysis of method with batching for monotone stochastic finite-sum variational inequalities (Q6124397) (← links)
• Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization (Q6126655) (← links)
• Robust Accelerated Primal-Dual Methods for Computing Saddle Points (Q6130545) (← links)
• Variable sample-size operator extrapolation algorithm for stochastic mixed variational inequalities (Q6131490) (← links)
• Optimal Algorithms for Stochastic Complementary Composite Minimization (Q6136660) (← links)
• A modified stochastic quasi-Newton algorithm for summing functions problem in machine learning (Q6138300) (← links)
• Quantifying outcome functions of linear programs: an approach based on interval-valued right-hand sides (Q6145049) (← links)
• Theoretical analysis of Adam using hyperparameters close to one without Lipschitz smoothness (Q6145578) (← links)
• Distribution-free algorithms for predictive stochastic programming in the presence of streaming data (Q6155066) (← links)
• Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise (Q6155875) (← links)
• Stochastic regularized Newton methods for nonlinear equations (Q6158978) (← links)
• Block mirror stochastic gradient method for stochastic optimization (Q6158991) (← links)
• A stochastic contraction mapping theorem (Q6161346) (← links)
• Accelerating stochastic sequential quadratic programming for equality constrained optimization using predictive variance reduction (Q6166650) (← links)
• Stochastic Saddle Point Problems with Decision-Dependent Distributions (Q6176418) (← links)
• Stochastic Fixed-Point Iterations for Nonexpansive Maps: Convergence and Error Bounds (Q6180255) (← links)
• A Decomposition Algorithm for Two-Stage Stochastic Programs with Nonconvex Recourse Functions (Q6188504) (← links)
• Reliable Error Estimates for Optimal Control of Linear Elliptic PDEs with Random Inputs (Q6188687) (← links)
• Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks (Q6190298) (← links)
• Randomized Lagrangian stochastic approximation for large-scale constrained stochastic Nash games (Q6191973) (← links)
• Sample Size Estimates for Risk-Neutral Semilinear PDE-Constrained Optimization (Q6195313) (← links)
• GANs training: A game and stochastic control approach (Q6196295) (← links)
• Stochastic gradient descent: where optimization meets machine learning (Q6200207) (← links)
• Variable sample-size optimistic mirror descent algorithm for stochastic mixed variational inequalities (Q6497046) (← links)
• When will gradient methods converge to max-margin classifier under ReLU models? (Q6541764) (← links)
• Variance reduced moving balls approximation method for smooth constrained minimization problems (Q6542460) (← links)
• Momentum-based accelerated mirror descent stochastic approximation for robust topology optimization under stochastic loads (Q6554079) (← links)
• Mini-batch stochastic subgradient for functional constrained optimization (Q6565290) (← links)
• General procedure to provide high-probability guarantees for stochastic saddle point problems (Q6569676) (← links)
• Tikhonov regularization as a nonparametric method for uncertainty quantification in aggregate data problems (Q6572168) (← links)
• A fast non-monotone line search for stochastic gradient descent (Q6572737) (← links)