6 citations · 13 across the 6 of their papers we have counts for
7 papers
A Noise-Aware Scalable Subspace Classical Optimizer for the Quantum Approximate Optimization Algorithm
Kwassi Joseph Dzahini, Jeffrey M. Larson, Matt Menickelly +1
We introduce ANASTAARS, a noise-aware scalable classical optimizer for variational quantum algorithms such as the quantum approximate optimization algorithm (QAOA). ANASTAARS lever…
Direct-search methods in the year 2025: Theoretical guarantees and algorithmic paradigms
K. J. Dzahini, F. Rinaldi, C. W. Royer +1
Optimizing a function without using derivatives is a challenging paradigm, that precludes from using classical algorithms from nonlinear optimization, and may thus seem intractable…
A class of sparse Johnson--Lindenstrauss transforms and analysis of their extreme singular values
Kwassi Joseph Dzahini, Stefan M. Wild
The Johnson--Lindenstrauss (JL) lemma is a powerful tool for dimensionality reduction in modern algorithm design. The lemma states that any set of high-dimensional points in a Eucl…
Stochastic trust-region algorithm in random subspaces with convergence and expected complexity analyses
Kwassi Joseph Dzahini, Stefan M. Wild
This work proposes a framework for large-scale stochastic derivative-free optimization (DFO) by introducing STARS, a trust-region method based on iterative minimization in random s…
Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates
Kwassi Joseph Dzahini, Michael Kokkolaras, Sébastien Le Digabel
This work introduces the StoMADS-PB algorithm for constrained stochastic blackbox optimization, which is an extension of the mesh adaptive direct-search (MADS) method originally de…
Expected complexity analysis of stochastic direct-search
Kwassi Joseph Dzahini
This work presents the convergence rate analysis of stochastic variants of the broad class of direct-search methods of directional type. It introduces an algorithm designed to opti…
StoMADS: Stochastic blackbox optimization using probabilistic estimates
Charles Audet, Kwassi Joseph Dzahini, Michael Kokkolaras +1
This work introduces StoMADS, a stochastic variant of the mesh adaptive direct-search (MADS) algorithm originally developed for deterministic blackbox optimization. StoMADS conside…