Cover Image

Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brevault, Loic, Balesdent, Mathieu
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to optimize: A tutorial for continuous and mixed-integer optimization
by: Chen, Xiaohan, et al.
Published: (2024)

A constrained optimization approach to improve robustness of neural networks
by: Zhao, Shudian, et al.
Published: (2024)

A mixed-categorical correlation kernel for Gaussian process
by: Saves, P., et al.
Published: (2022)

Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design
by: Saves, Paul, et al.
Published: (2025)

Learning solutions to some toy constrained optimization problems in infinite dimensional Hilbert spaces
by: Mandal, Pinak
Published: (2024)

Multi-fidelity approaches for general constrained Bayesian optimization with application to aircraft design
by: Cordelier, Oihan, et al.
Published: (2026)

High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft
by: Saves, Paul, et al.
Published: (2023)

BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantification
by: Lu, Yen-An, et al.
Published: (2024)

Learning based convex approximation for constrained parametric optimization
by: Liu, Kang, et al.
Published: (2025)

The inexact power augmented Lagrangian method for constrained nonconvex optimization
by: Bodard, Alexander, et al.
Published: (2024)

Convex mixed-integer optimization with Frank-Wolfe methods
by: Hendrych, Deborah, et al.
Published: (2022)

Group-blind optimal transport to group parity and its constrained variants
by: Zhou, Quan, et al.
Published: (2023)

Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization
by: Li, Yuchen, et al.
Published: (2023)

Block majorization-minimization with diminishing radius for constrained nonsmooth nonconvex optimization
by: Lyu, Hanbaek, et al.
Published: (2020)

A safe exploration approach to constrained Markov decision processes
by: Ni, Tingting, et al.
Published: (2023)

On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem
by: Ding, Kuangyu, et al.
Published: (2025)

Multi-objective Bayesian Optimization With Mixed-categorical Design Variables for Expensive-to-evaluate Aeronautical Applications
by: Bartoli, Nathalie, et al.
Published: (2025)

A distribution-free mixed-integer optimization approach to hierarchical modelling of clustered and longitudinal data
by: Sankaranarayanan, Madhav, et al.
Published: (2023)

Towards a connection between the capacitated vehicle routing problem and the constrained centroid-based clustering
by: Abdellaoui, Abdelhakim, et al.
Published: (2024)

Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian
by: He, Chuan, et al.
Published: (2023)

Stochastic global optimization of continuous functions via random walks on Grassmannians
by: Gupta, Kartik, et al.
Published: (2026)

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
by: Dagréou, Mathieu, et al.
Published: (2022)

qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling
by: Renganathan, Ashwin, et al.
Published: (2023)

"Over-optimizing" for Normality: Budget-constrained Uncertainty Quantification for Contextual Decision-making
by: Wang, Yanyuan, et al.
Published: (2025)

Towards safe Bayesian optimization with Wiener kernel regression
by: Molodchyk, Oleksii, et al.
Published: (2024)

PACSBO: Probably approximately correct safe Bayesian optimization
by: Tokmak, Abdullah, et al.
Published: (2024)

Manifold constrained steepest descent
by: Yang, Kaiwei, et al.
Published: (2026)

Formulations and scalability of neural network surrogates in nonlinear optimization problems
by: Parker, Robert B., et al.
Published: (2024)

On characterizing optimal learning trajectories in a class of learning problems
by: Befekadu, Getachew K
Published: (2025)

An analysis of optimization problems involving ReLU neural networks
by: Plate, Christoph, et al.
Published: (2025)

Safe Bayesian optimization across noise models via scenario programming
by: Tokmak, Abdullah, et al.
Published: (2025)

Bayesian optimization as a flexible and efficient design framework for sustainable process systems
by: Paulson, Joel A., et al.
Published: (2024)

Gromov-Wasserstein and optimal transport: from assignment problems to probabilistic numeric
by: Seyedi, Iman, et al.
Published: (2025)

Sinkhorn algorithms and linear programming solvers for optimal partial transport problems
by: Bai, Yikun
Published: (2024)

TS-RSR: A provably efficient approach for batch Bayesian Optimization
by: Ren, Zhaolin, et al.
Published: (2024)

A minimax optimal control approach for robust neural ODEs
by: Cipriani, Cristina, et al.
Published: (2023)

Buffered AUC maximization for scoring systems via mixed-integer optimization
by: Shiina, Moe, et al.
Published: (2026)

BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty
by: Kudva, Akshay, et al.
Published: (2025)

Continuous and discrete-time accelerated methods for an inequality constrained convex optimization problem
by: Liu, Juan, et al.
Published: (2024)

Solving a class of stochastic optimal control problems by physics-informed neural networks
by: Jiao, Zhe, et al.
Published: (2024)