6 papers · 1 filter
An objective-function-free algorithm for nonconvex stochastic optimization with deterministic equality and inequality constraints
S. Gratton, Ph. L. Toint
An algorithm is proposed for solving optimization problems with stochastic objective and deterministic equality and inequality constraints. This algorithm is objective-function-fre…
An objective-function-free algorithm for general smooth constrained optimization
S. Bellavia, S. Gratton, B. Morini +1
A new algorithm for smooth constrained optimization is proposed that never computes the value of the problem's objective function and that handles both equality and inequality cons…
Iteration complexity of the Difference-of-Convex Algorithm for unconstrained optimization: a simple proof
Serge Gratton, Philippe L. Toint
We propose a simple proof of the worst-case iteration complexity for the Difference of Convex functions Algorithm (DCA) for unconstrained minimization, showing that the global rate…
A Simple First-Order Algorithm for Full-Rank Equality Constrained Optimization
Serge Gratton, Philippe L. Toint
A very simple first-order algorithm is proposed for solving nonlinear optimization problems with deterministic nonlinear equality constraints. This algorithm adaptively selects ste…
Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization
Serge Gratton, Alena Kopaničáková, Philippe Toint
Two OFFO (Objective-Function Free Optimization) noise tolerant algorithms are presented that handle bound constraints, inexact gradients and use second-order information when avail…
Refining asymptotic complexity bounds for nonconvex optimization methods, including why steepest descent is rather than
Serge Gratton, Chee-Khian Sim, Philippe L. Toint
We revisit the standard ``telescoping sum'' argument ubiquitous in the final steps of analyzing evaluation complexity of algorithms for smooth nonconvex optimization, and obtain a…