10 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…
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…
A Fast Newton Method Under Local Lipschitz Smoothness
Serge Gratton, Sadok Jerad, Philippe L. Toint
A new, fast second-order method is proposed that achieves the optimal complexity to obtain first-order -stationary points. Crucial…
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…
Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization
Serge Gratton, Alena KopaniÄáková, 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…
prunAdag: an adaptive pruning-aware gradient method
Margherita Porcelli, Giovanni Seraghiti, Philippe L. Toint
A pruning-aware adaptive gradient method is proposed which classifies the variables in two sets before updating them using different strategies. This technique extends the ``releva…