Cover Image

Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Raponi, Elena, Carraz, Nathanael Rakotonirina, Rapin, Jérémy, Doerr, Carola, Teytaud, Olivier
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MemoryPrompt: A Light Wrapper to Improve Context Tracking in Pre-trained Language Models
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2024)

Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
by: Santoni, Maria Laura, et al.
Published: (2023)

Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization
by: Santoni, Maria Laura, et al.
Published: (2024)

Evil twins are not that evil: Qualitative insights into machine-generated prompts
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2024)

MECHBench: A Set of Black-Box Optimization Benchmarks originated from Structural Mechanics
by: Rodríguez, Iván Olarte, et al.
Published: (2025)

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
by: Tørring, Jacob O., et al.
Published: (2024)

Similarity-based Portfolio Construction for Black-box Optimization
by: Dinu, Catalin-Viorel, et al.
Published: (2026)

HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI Gym
by: La, Ngoc, et al.
Published: (2025)

A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization
by: Cenikj, Gjorgjina, et al.
Published: (2024)

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization
by: Dietrich, Konstantin, et al.
Published: (2024)

Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms
by: López-Ibáñez, Manuel, et al.
Published: (2024)

Geometric Learning in Black-Box Optimization: A GNN Framework for Algorithm Performance Prediction
by: Kostovska, Ana, et al.
Published: (2025)

Feasibility-Driven Trust Region Bayesian Optimization
by: Ascia, Paolo, et al.
Published: (2025)

Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
by: Dietrich, Konstantin, et al.
Published: (2024)

Optimizing Kernel Discrepancies via Subset Selection
by: Chen, Deyao, et al.
Published: (2025)

Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2026)

OpenBox: A Python Toolkit for Generalized Black-box Optimization
by: Jiang, Huaijun, et al.
Published: (2023)

An Open-Source Training Dataset for Foundation Models for Black-box Optimization
by: Klein, Aaron, et al.
Published: (2026)

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning
by: Salaorni, Davide, et al.
Published: (2025)

On Sarcasm Detection with OpenAI GPT-based Models
by: Gole, Montgomery, et al.
Published: (2023)

SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems
by: Ramanujam, Asha, et al.
Published: (2025)

Cascading CMA-ES Instances for Generating Input-diverse Solution Batches
by: Santoni, Maria Laura, et al.
Published: (2025)

LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms
by: Li, Wenhu, et al.
Published: (2025)

HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization
by: Chen, Hongzheng, et al.
Published: (2025)

Collaborative and Federated Black-box Optimization: A Bayesian Optimization Perspective
by: Kontar, Raed Al
Published: (2024)

How Sequential Algorithm Portfolios can benefit Black Box Optimization
by: Dinu, Catalin-Viorel, et al.
Published: (2026)

Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+($λ$,$λ$))-GA
by: Nguyen, Tai, et al.
Published: (2025)

EduGym: An Environment and Notebook Suite for Reinforcement Learning Education
by: Moerland, Thomas M., et al.
Published: (2023)

CPT: Consistent Proxy Tuning for Black-box Optimization
by: He, Yuanyang, et al.
Published: (2024)

VOPy: A Framework for Black-box Vector Optimization
by: Yıldırım, Yaşar Cahit, et al.
Published: (2024)

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
by: Chew, Ruth Wan Theng, et al.
Published: (2026)

Black-box Optimization of LLM Outputs by Asking for Directions
by: Zhang, Jie, et al.
Published: (2025)

Direct Acquisition Optimization for Low-Budget Active Learning
by: Zhao, Zhuokai, et al.
Published: (2024)

Locality-aware Surrogates for Gradient-based Black-box Optimization
by: Momeni, Ali, et al.
Published: (2025)

Mixture of Experts in Image Classification: What's the Sweet Spot?
by: Videau, Mathurin, et al.
Published: (2024)

Evolutionary Pre-Prompt Optimization for Mathematical Reasoning
by: Videau, Mathurin, et al.
Published: (2024)

Black-box Optimization with Simultaneous Statistical Inference for Optimal Performance
by: Lian, Teng, et al.
Published: (2025)

On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability
by: Wang, Kevin, et al.
Published: (2024)

Task-free Adaptive Meta Black-box Optimization
by: Wang, Chao, et al.
Published: (2026)

Hyperband-based Bayesian Optimization for Black-box Prompt Selection
by: Schneider, Lennart, et al.
Published: (2024)