Global convergence rate analysis of unconstrained optimization methods based on probabilistic models

Direct Search Based on Probabilistic Descent

(2015) S. Gratton et al.   SIAM JOURNAL ON OPTIMIZATION

Convergence of Trust-Region Methods Based on Probabilistic Models

(2014) A. S. Bandeira et al.   SIAM JOURNAL ON OPTIMIZATION

First-order methods of smooth convex optimization with inexact oracle

(2013) Olivier Devolder et al.   MATHEMATICAL PROGRAMMING

Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming

(2013) Saeed Ghadimi et al.   SIAM JOURNAL ON OPTIMIZATION

Sample size selection in optimization methods for machine learning

(2012) Richard H. Byrd et al.   MATHEMATICAL PROGRAMMING

On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization

(2012) Coralia Cartis et al.   SIAM JOURNAL ON OPTIMIZATION

Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity

(2010) Coralia Cartis et al.   MATHEMATICAL PROGRAMMING

Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results

(2009) Coralia Cartis et al.   MATHEMATICAL PROGRAMMING