Results 11 to 20 of about 56,129 (265)
Journal of Fluid Science and Technology, 2021 We attempt to optimize the control parameters of traveling wave-like wall deformation for turbulent friction drag reduction using the Bayesian optimization. The Bayesian optimization is an optimization method based on stochastic processes, and it is good
Yusuke NABAE, Koji FUKAGATA
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Advances in Neural Information Processing Systems 36, 2023 Accepted to NeurIPS ...
Zhongxiang Dai +5 more
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Entropy, 2023 In order to reduce the errors caused by the idealization of the conventional analytical model in the transient planar source (TPS) method, a finite element model that more closely represents the actual heat transfer process was constructed.
Hualin Ji +4 more
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Hybrid algorithm of Bayesian optimization and evolutionary algorithm in crystal structure prediction
Science and Technology of Advanced Materials: Methods, 2022 We propose a highly efficient searching algorithm in crystal structure prediction. The searching algorithm is a hybrid of the evolutionary algorithm and Bayesian optimization. The evolutionary algorithm is widely used in crystal structure prediction, and
Tomoki Yamashita +4 more
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CoRR, 2020 This paper studies the problem of globally optimizing a variable of interest that is part of a causal model in which a sequence of interventions can be performed. This problem arises in biology, operational research, communications and, more generally, in all fields where the goal is to optimize an output metric of a system of interconnected nodes. Our
Virginia Aglietti +3 more
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Bayesian optimization for computationally extensive probability distributions. [PDF]
PLoS ONE, 2018 An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique.
Ryo Tamura, Koji Hukushima
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Optimizing Automated Trading Systems with Deep Reinforcement Learning
Algorithms, 2023 In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward ...
Minh Tran, Duc Pham-Hi, Marc Bui
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HYPERPARAMETER OPTIMIZATION BASED ON A PRIORI AND A POSTERIORI KNOWLEDGE ABOUT CLASSIFICATION PROBLEM [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2020 Subject of Research. The paper deals with Bayesian method for hyperparameter optimization of algorithms, used in machine learning for classification problems.
Valentina S. Smirnova +3 more
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Bayesian Optimization for QAOA
IEEE Transactions on Quantum Engineering, 2023 The quantum approximate optimization algorithm (QAOA) adopts a hybrid quantum-classical approach to find approximate solutions to variational optimization problems.
Simone Tibaldi +3 more
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Application of Improved LightGBM Model in Blood Glucose Prediction
Applied Sciences, 2020 In recent years, with increasing social pressure and irregular schedules, many people have developed unhealthy eating habits, which has resulted in an increasing number of patients with diabetes, a disease that cannot be cured under the current medical ...
Yan Wang, Tao Wang
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