Results 11 to 20 of about 73,328 (265)
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 ...
Vishnu TV +4 more
openaire +2 more sources
Diffusion Models for Black-Box Optimization
CoRR, 2023 International Conference on Machine Learning ...
Siddarth Krishnamoorthy +2 more
openaire +3 more sources
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
IEEE Open Journal of the Computer Society, 2020 Widely deployed smart cameras are generating a large amount of video data and capable of processing frames on devices. Empowered by edge computing, the video data can also be offloaded to edge servers for processing.
Yang Deng, Tao Han, Nirwan Ansari
doaj +1 more source
OpenBox: A Generalized Black-box Optimization Service [PDF]
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021 Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, engineering, physics, and experimental design. However, it remains a challenge for users to apply BBO methods to their problems at hand with existing software packages, in terms of applicability, performance, and efficiency.
Yang Li 0106 +11 more
openaire +2 more sources
On the Design of a Class of Rotary Compressors Using Bayesian Optimization
Machines, 2021 The optimization process of compressors is usually regarded as a ‘black-box’ problem, in which the mathematical form underlying the relationship between design parameters and the design objective is impractical and costly to be obtained.
Kui Lu +2 more
doaj +1 more source
Adaptive divergence for rapid adversarial optimization [PDF]
PeerJ Computer Science, 2020 Adversarial Optimization provides a reliable, practical way to match two implicitly defined distributions, one of which is typically represented by a sample of real data, and the other is represented by a parameterized generator.
Maxim Borisyak +2 more
doaj +2 more sources
Generative Pretraining for Black-Box Optimization
CoRR, 2022 International Conference for Machine Learning 2023 NeurIPS Workshop for Foundational Models for Decision Making (Oral ...
Siddarth Krishnamoorthy +2 more
openaire +3 more sources