Analysis of biased stochastic gradient descent using sequential semidefinite programs

Optimization Methods for Large-Scale Machine Learning

(2018) Léon Bottou et al.   SIAM REVIEW

Exact Worst-Case Performance of First-Order Methods for Composite Convex Optimization

(2017) Adrien B. Taylor et al.   SIAM JOURNAL ON OPTIMIZATION

Guaranteed Matrix Completion via Non-Convex Factorization

(2016) Ruoyu Sun et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

Smooth strongly convex interpolation and exact worst-case performance of first-order methods

(2016) Adrien B. Taylor et al.   MATHEMATICAL PROGRAMMING

Minimizing finite sums with the stochastic average gradient

(2016) Mark Schmidt et al.   MATHEMATICAL PROGRAMMING

On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions

(2016) Etienne de Klerk et al.   Optimization Letters

Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints

(2016) Laurent Lessard et al.   SIAM JOURNAL ON OPTIMIZATION

Performance of first-order methods for smooth convex minimization: a novel approach

(2013) Yoel Drori et al.   MATHEMATICAL PROGRAMMING

First-order methods of smooth convex optimization with inexact oracle

(2013) Olivier Devolder et al.   MATHEMATICAL PROGRAMMING

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

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

Smooth Optimization with Approximate Gradient

(2008) Alexandre d'Aspremont   SIAM JOURNAL ON OPTIMIZATION