Youssef Diouane

Adjunct Professor

Polytechnique Montréal

Canada

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Youssef Diouane is an Adjunct Professor at Polytechnique Montréal, Canada. His research focuses on advanced optimization techniques and Gaussian processes, as reflected in his recent publications. Notable areas of interest include mixed-variable domains, Bayesian optimization, and surrogate modeling methodologies.

Articles (18)

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2025

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2021

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2021

Collaborators (5)

Elisa Riccietti

Associate professor

École normale supérieure de Lyon

FRANCE

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John Hwang

University of California, San Diego

UNITED STATES

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Ana Luísa Custodio

Professor Associado

NOVA FCT

PORTUGAL

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Rohollah Garmanjani

Universidade de Évora Departamento de Matemática

PORTUGAL

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Clément W. Royer

FRANCE

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Youssef Diouane

Research Interests

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About

Articles (18)

A distance for mixed-variable and hierarchical domains with meta variables

A Stochastic iteratively regularized Gauss–Newton method

High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings

SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes

High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft

A graph-structured distance for mixed-variable domains with meta variables

Inexact direct-search methods for bilevel optimization problems

Impact of correlated observation errors on the conditioning of variational data assimilation problems

TREGO: a trust-region framework for efficient global optimization

A mixed-categorical correlation kernel for Gaussian process

A Subsampling Line-Search Method with Second-Order Results

An outer approximation bi-level framework for mixed categorical structural optimization problems

A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results

A Nonmonotone Matrix-Free Algorithm for Nonlinear Equality-Constrained Least-Squares Problems

A Variational Adjoint Approach on Wide-Angle Parabolic Equation for Refractivity Inversion

Worst-Case Complexity Bounds of Directional Direct-Search Methods for Multiobjective Optimization

A merit function approach for evolution strategies

Complexity iteration analysis for strongly convex multi-objective optimization using a Newton path-following procedure

Collaborators (5)

Elisa Riccietti

John Hwang

Ana Luísa Custodio

Rohollah Garmanjani

Clément W. Royer

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