Black-Box Optimization

Ask about this topic

Overview

Black-box optimization studies how to choose inputs that maximize or minimize an objective when its internal workings or gradients are unavailable, often because each evaluation is costly. Common approaches include Gaussian-process Bayesian optimization, evolutionary strategies such as CMA-ES and differential evolution, and bandit or partitioning methods that balance exploration with refinement. Surrogate models, multi-fidelity evaluations, and learned or generative proposals extend these methods to noisy, constrained, discrete, and high-dimensional tasks, including scientific design and system tuning. Benchmarks such as COCO/BBOB and CEC help compare methods, but performance often depends on the problem and evaluation budget, leaving robust transfer and fair comparisons across settings as central challenges.

Latest papers

CardsList

177 papers25 papers in the last four weeks, up 25% on the four weeks before. 0.1% of all new papers.

  1. Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding

    May 6, 2026Taiga Hayashi, Yuya Seki, Kotaro Terada +3Black-Box Optimization

    1Graduate School of Science and Technology, Keio University, Yokohama, Kanagawa 223-8522, Japan · 2Keio Sustainable Quantum Artificial Intelligence Center, Keio University, Minato-ku, Tokyo 108-8345, Japan · 3Quanmatic Inc., Shinjuku-ku, Tokyo 162-0042, Japan +2

  2. Bandits attack function optimization

    May 5, 2026Philippe Preux, Rémi Munos, Michal ValkoBlack-Box OptimizationGlobal Optimization

    Université de Lille, LIFL (UMR 8022 CNRS), and INRIA, France · INRIA, and LIFL, Lille, France

  3. Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

    May 4, 2026Yash Madhwal, Arseny Bolotnikov, Mark Prikhno +5Bayesian OptimizationBlack-Box Optimization

    Skolkovo Institute of Science and Technology, Moscow, Russia · HSE University, Moscow, Russia · Sberbank PJSC, Moscow, Russia +4

  4. Black-box optimization of noisy functions with unknown smoothness

    May 4, 2026Jean-Bastien Grill, Michal Valko, Rémi MunosBlack-Box OptimizationZeroth-Order Optimization

    SequeL team, INRIA Lille - Nord Europe, France · Google DeepMind, UK∗

  5. Training Non-Differentiable Networks via Optimal Transport

    May 3, 2026An T. LeBlack-Box OptimizationNeural Network Optimization

    Center for AI Research, VinUniversity, Vietnam · Intelligent Autonomous Systems, TU Darmstadt, Germany

  6. Learning to Act and Cooperate for Distributed Black-Box Consensus Optimization

    May 1, 2026Zi-Bo Qin, Feng-Feng Wei, Tai-You Chen +1Multi-Agent System OptimizationMulti-Agent Coordination

    School of Computer Science and Engineering, South China University of Technology, Guangzhou, China.

  7. Bayesian Optimization in Linear Time

    Apr 30, 2026Jesse Schneider, William J. WelchBayesian OptimizationBlack-Box Optimization

    Department of Statistics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

  8. Relation Reasoning with LLMs in Expensive Optimization

    Apr 30, 2026Ye Lu, Bingdong Li, Aimin Zhou +1Surrogate-Assisted OptimizationBlack-Box Optimization

    Shanghai Institute of Al for Education, East China Normal University, Shanghai 200062, China

  9. RCMAES: A Robust CMA-ES Variant for CEC2026 Competition

    Apr 29, 2026Khoirul Faiq Muzakka, Sören Möller, Martin FinsterbuschEvolutionary OptimizationBlack-Box Optimization

    Institute of Energy Materials and Devices (IMD-2), Forschungszentrum Jülich GmbH, Germany

  10. Feasible-First Exploration for Constrained ML Deployment Optimization in Crash-Prone Hierarchical Search Spaces

    Apr 27, 2026Christian LysenstøenBayesian OptimizationBlack-Box Optimization

    Department of Electrical Engineering and Computer Sciences University of California, Berkeley

  11. Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions

    Apr 27, 2026Molena HuynhBlack-Box OptimizationCombinatorial Optimization

    North Carolina State University

  12. Rethinking Trust Region Bayesian Optimization in High Dimensions

    Apr 24, 2026Wei-Ting Tang, Joel A. PaulsonBayesian OptimizationBlack-Box Optimization

    University of Wisconsin–Madison

  13. BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference

    Apr 23, 2026Beomchang Kim, Subhrajyoty Roy, Priyam DasStiefel Manifold OptimizationBlack-Box Optimization

    Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA · Department of Statistics and Data Science, Washington University in St. Louis,[math.OC] St. Louis, MO, USA

  14. Similarity-based Portfolio Construction for Black-box Optimization

    Apr 20, 2026Catalin-Viorel Dinu, Diederick Vermetten, Carola DoerrAlgorithm SelectionBlack-Box Optimization

    Sorbonne Université, CNRS, LIP6

  15. RASP-Tuner: Retrieval-Augmented Soft Prompts for Context-Aware Black-Box Optimization in Non-Stationary Environments

    Apr 20, 2026Enze PanSurrogate-Assisted OptimizationBlack-Box Optimization

    Department of Computer Science, The University of Hong Kong.

  16. SLO-Guard: Crash-Aware, Budget-Consistent Autotuning for SLO-Constrained LLM Serving

    Apr 19, 2026Christian LysenstøenLLM Inference EfficiencyLLM Serving

    Inland Norway University of Applied Sciences · Visiting Student, University of California, Berkeley

  17. Adaptive multi-fidelity optimization with fast learning rates

    Apr 17, 2026Come Fiegel, Victor Gabillon, Michal ValkoMulti-Fidelity OptimizationBlack-Box Optimization

    ´Ecole Normale Sup´erieure, Paris · Huawei R&D, UK · Inria Lille

  18. Stein Variational Black-Box Combinatorial Optimization

    Apr 17, 2026Thomas Landais, Olivier Goudet, Adrien Goëffon +2Stochastic OptimizationBlack-Box Optimization

    LERIA, Université d’Angers, 2 Boulevard Lavoisier, Angers 49045, France

  19. Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning

    Apr 17, 2026Jorge Sánchez, Guadalupe García-Isla, Sandra Perez-Herrero +2Black-Box OptimizationMetaheuristic Optimization

    Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politécnica de València, Camino de Vera s/n, 46022 Valencia, Spain

  20. Optimization with SpotOptim

    Apr 15, 2026Thomas Bartz-BeielsteinBlack-Box OptimizationSurrogate-Assisted Optimization

    Bartz & Bartz GmbH, 51643 Gummersbach, Germany

  21. Does Dimensionality Reduction via Random Projections Preserve Landscape Features?

    Apr 14, 2026Iván Olarte Rodríguez, Anja Jankovic, Thomas Bäck +1Black-Box OptimizationRandomized Sketching

    Leiden Institute of Advanced Computer Science, Leiden University · Leiden, The Netherlands · RTWH Aachen University +1

  22. Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks

    Apr 14, 2026Azza Fadhel, The Hung Tran, Trong Nghia Hoang +1Black-Box OptimizationSurrogate-Assisted Optimization

    School of EECS, Washington State University, Pullman, WA, USA

  23. Obtaining Partition Crossover masks using Statistical Linkage Learning for solving noised optimization problems with hidden variable dependency structure

    Apr 13, 2026M. W. Przewozniczek, B. Frej, M. M. Komarnicki +2Evolutionary OptimizationBlack-Box Optimization

    Wroclaw Univ. of Science and Techn. Wroclaw, Poland · University of São Paulo Ribeirão Preto, Brazil

  24. Geometric Probing for Algorithm Selection in Continuous Black-Box Optimization

    Apr 10, 2026Jiabao Brad Wang, Xiang Shi, Yiliang Yuan +1Algorithm SelectionBlack-Box Optimization

    Duke Kunshan University, Kunshan, Jiangsu, China · Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  25. Loop-Extrusion Linkage: Spectral Ordering and Interval-Based Structure Discovery for Continuous Optimization

    Apr 5, 2026Eren UnluMetaheuristic OptimizationBlack-Box Optimization

    Globeholder, Paris, France

  26. One-Shot Localisation of the Global Minimum of a Noisy One-Dimensional Function: A Controlled Comparison of an Iterative Neural Minimizer, Set Transformers and Classical Estimators

    Apr 4, 2026Qusay Muzaffar, David Levin, Michael WermanBlack-Box OptimizationZeroth-Order Optimization

    Department of Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel · Department of Applied Mathematics, Tel Aviv University, Tel Aviv, Israel

  27. Accelerating Black-Box Bilevel Optimization with Rank-Based Upper-Level Value Function Approximation

    Apr 3, 2026Marc Ong, Youhei AkimotoBilevel OptimizationBlack-Box Optimization

    University of Tsukuba Tsukuba, Ibaraki, JAPAN · University of Tsukuba & RIKEN AIP Tsukuba, Ibaraki, JAPAN

  28. Greedy Is a Strong Default: Agents as Iterative Optimizers

    Mar 28, 2026Yitao LiLarge Language Model-Guided OptimizationBlack-Box Optimization

  29. Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions

    Mar 25, 2026Abhilasha Saroj, Shaked Regev, Guanhao Xu +3Bayesian OptimizationBlack-Box Optimization

  30. Can an Actor-Critic Optimization Framework Improve Analog Design?

    Mar 25, 2026Sounak Dutta, Fin Amin, Sushil Panda +3Analog Circuit SizingElectronic Design Automation

    North Carolina State University, Department of Electrical and Computer Engineering, Raleigh, North Carolina, USA