Stochastic gradient descent for semilinear elliptic equations with uncertainties

Sequential function approximation with noisy data

(2018) Yeonjong Shin et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Optimization Methods for Large-Scale Machine Learning

(2018) Léon Bottou et al.   SIAM REVIEW

Application of Quasi-Monte Carlo Methods to Elliptic PDEs with Random Diffusion Coefficients: A Survey of Analysis and Implementation

(2016) Frances Y. Kuo et al.   FOUNDATIONS OF COMPUTATIONAL MATHEMATICS

On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems

(2015) R.V. Field et al.   PROBABILISTIC ENGINEERING MECHANICS

Stochastic finite element methods for partial differential equations with random input data

(2014) Max D. Gunzburger et al.   ACTA NUMERICA

Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization

(2012) Alekh Agarwal et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

Robust Stochastic Approximation Approach to Stochastic Programming

(2009) A. Nemirovski et al.   SIAM JOURNAL ON OPTIMIZATION

An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

(2008) F. Nobile et al.   SIAM JOURNAL ON NUMERICAL ANALYSIS

A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

(2008) F. Nobile et al.   SIAM JOURNAL ON NUMERICAL ANALYSIS