Results 21 to 30 of about 226,052 (275)
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems [PDF]
GECCO Companion, 2023 Performance complementarity of solvers available to tackle black-box optimization problems gives rise to the important task of algorithm selection (AS).
Ana Kostovska +5 more
semanticscholar +1 more source
PyBADS: Fast and robust black-box optimization in Python [PDF]
Journal of Open Source Software, 2023 PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for fast and robust black-box optimization (Acerbi and Ma 2017).
Gurjeet Singh, Luigi Acerbi
semanticscholar +1 more source
Journal of Hydroinformatics, 2023 In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results.
Tiexiang Mo, Shanshan Li, Guodong Li
doaj +1 more source
Discovering Evolution Strategies via Meta-Black-Box Optimization [PDF]
International Conference on Learning Representations, 2022 Optimizing functions without access to gradients is the remit of black-box methods such as evolution strategies. While highly general, their learning dynamics are often times heuristic and inflexible --- exactly the limitations that meta-learning can ...
R. Lange +7 more
semanticscholar +1 more source
Exploration of new chemical materials using black-box optimization with the D-wave quantum annealer
Frontiers in Computer Science, 2023 In materials informatics, searching for chemical materials with desired properties is challenging due to the vastness of the chemical space. Moreover, the high cost of evaluating properties necessitates a search with a few clues.
Mikiya Doi +7 more
doaj +1 more source
Configuration Optimization of Hadoop Based on Recursive Random Sampling [PDF]
Jisuanji gongcheng, 2016 Hadoop platform has over 200 configuration parameters,it can improve the performance of the system by deploying these parameters in reason.Aiming at the optimization of Hadoop configuration parameters problem,a black box optimization strategy based on ...
ZHU Chunxiang,CHEN Shiping,CHEN Mingang
doaj +1 more source
Black-Box for Blockchain Parameters Adjustment
IEEE Access, 2022 This paper introduces a function for blockchain performance evaluation as a black-box. The function runs the Solana blockchain test network with the only differences between the main network in a configuration file and the physical network to operate in.
Vladislav Amelin +5 more
doaj +1 more source
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2023 The application of machine learning (ML) models to the analysis of optimization algorithms requires the representation of optimization problems using numerical features.
Gjorgjina Cenikj +4 more
semanticscholar +1 more source
CMA-ES with margin: lower-bounding marginal probability for mixed-integer black-box optimization [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2022 This study targets the mixed-integer black-box optimization (MI-BBO) problem where continuous and integer variables should be optimized simultaneously.
Ryoki Hamano +3 more
semanticscholar +1 more source
Meta-Learning for Black-Box Optimization [PDF]
, 2020 Recently, neural networks trained as optimizers under the "learning to learn" or meta-learning framework have been shown to be effective for a broad range of optimization tasks including derivative-free black-box function optimization. Recurrent neural networks (RNNs) trained to optimize a diverse set of synthetic non-convex differentiable functions ...
TV, Vishnu +4 more
openaire +2 more sources