Search Results - Optimization Methods in Machine Learning

Gradient Optimization Methods in Machine Learning for the Identification of Dynamic Systems Parameters by Panteleev, A.V., Lobanov, A.V.

“… The parallelepiped type constraints are imposed on the parameter values. To solve the optimization problem, it is proposed to use gradient optimization methods used in machine learning procedures…”
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A Survey of Optimization Methods From a Machine Learning Perspective by Sun, Shiliang, Cao, Zehui, Zhu, Han, Zhao, Jing

“… With the exponential growth of data amount and the increase of model complexity, optimization methods in machine learning face more and more…”
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Forecasting the Stock Price of Listed Innovative SMEs Using Machine Learning Methods Based on Bayesian optimization: Evidence from China by Liu, Wei, Suzuki, Yoshihisa, Du, Shuyi

“… Therefore, this study takes the Chinese market as an example, after constructing 34 determinants that affect the stock price, the RF, DNN, GBDT, and Adaboost models under Bayesian optimization…”
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On Hyperparameter Optimization of Machine Learning Methods Using a Bayesian Optimization Algorithm to Predict Work Travel Mode Choice by Aghaabbasi, Mahdi, Ali, Mujahid, Jasinski, Michal, Leonowicz, Zbigniew, Novak, Tomas

“… work. In the prediction of travel mode selection, machine learning methods are commonly employed. To fit a machine-learning model to various challenges, the hyperparameters must be tweaked…”
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Breaking the mold of simulation-optimization: Direct forward machine learning methods for groundwater contaminant source identification by Wang, Chaoqi, Dou, Zhi, Zhu, Yan, Yang, Ze, Zou, Zhihan

“…•The first Direct Forward Machine Learning (DFML) method can accurately estimate eight parameters related to contaminant source location, historical release intensity, and aquifer properties…”
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Machine-Learning-Based Optimization Method for Polarization-Rotation Element in Broadband and High-Aperture-Efficiency Metalens Antenna by Yang, Ruoyang, Wu, Jie, Zhao, Jianing, Li, Hao, Li, Tianming, Li, Fang, Wang, Haiyang, Zhou, Yihong, Hu, Biao, Fu, Cheng

“…A machine-learning-based method is utilized to design and optimize the polarization rotation element (PRE…”
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Optimization methods in machine learning: Theory and applications by Saha, Ankan

“…We look at the integral role played by convex optimization in various machine learning problems…”
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Bi-objective ship speed optimization based on machine learning method and discrete optimization idea by Li, Xiaohe, Ding, Kunping, Xie, Xianwei, Yao, Yu, Zhao, Xin, Jin, Jianhai, Sun, Baozhi

“… A practical bi-objective speed optimization (BSO) algorithm for container ships is developed based on the variable weight idea, the discrete optimization idea, and the ideal point method to meet the urgent needs of shipping companies to improve…”
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Knowledge distillation: A good teacher is patient and consistent by Beyer, Lucas, Zhai, Xiaohua, Royer, Amelie, Markeeva, Larisa, Anil, Rohan, Kolesnikov, Alexander

“… Throughout our empirical investigation we do not aim to necessarily propose a new method, but strive to identify a robust and effective recipe for making state-of-the-art large scale models affordable in practice…”
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Applying machine learning optimization methods to the production of a quantum gas by Barker, A J, Style, H, Luksch, K, Sunami, S, Garrick, D, Hill, F, Foot, C J, Bentine, E

“…We apply three machine learning strategies to optimize the atomic cooling processes utilized in the production of a Bose-Einstein condensate (BEC…”
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Hybrid approaches to optimization and machine learning methods: a systematic literature review by Azevedo, Beatriz Flamia, Rocha, Ana Maria A. C., Pereira, Ana I.

“… (optimization and machine learning) to integrate methodologies and make them more efficient. This paper presents an extensive systematic and bibliometric literature review…”
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Operator Theory for Analysis of Convex Optimization Methods in Machine Learning by Gallagher, Patrick W

“…As machine learning has more closely interacted with optimization, the concept of convexity has loomed large…”
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Prediction of effluent total nitrogen and energy consumption in wastewater treatment plants: Bayesian optimization machine learning methods by Ye, Gang, Wan, Jinquan, Deng, Zhicheng, Wang, Yan, Chen, Jian, Zhu, Bin, Ji, Shiming

“… The prediction performance of machine learning methods under different random seeds was explored, the moving average method was used for data amplification, and the Bayesian algorithm was used…”
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Waste Heat Recuperation in Advanced Supercritical CO2 Power Cycles with Organic Rankine Cycle Integration & Optimization Using Machine Learning Methods by Turja, Asif Iqbal, Sadat, Khandekar Nazmus, Hasan, Md. Mahmudul, Khan, Yasin, Ehsan, Md. Monjurul

“… Utilizing a thermodynamic model-derived dataset, various machine learning algorithms, including Random Forest, XGBoost, and Artificial Neural Network are employed for prediction, evaluation and optimization…”
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Gas–Liquid Two-Phase Flow Measurement Based on Optical Flow Method with Machine Learning Optimization Model by Wang, Junxian, Huang, Zhenwei, Xu, Ya, Xie, Dailiang

“… Machine learning algorithms are employed for the prediction…”
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Sample size selection in optimization methods for machine learning by Byrd, Richard H., Chin, Gillian M., Nocedal, Jorge, Wu, Yuchen

“…This paper presents a methodology for using varying sample sizes in batch-type optimization methods for large-scale machine learning problems…”
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CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method by Zhang, Leili, Domeniconi, Giacomo, Yang, Chih-Chieh, Kang, Seung-gu, Zhou, Ruhong, Cong, Guojing

“… We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots…”
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Glioma grade detection using grasshopper optimization algorithm‐optimized machine learning methods: The Cancer Imaging Archive study by Hedyehzadeh, Mohammadreza, Maghooli, Keivan, MomenGharibvand, Mohammad

“…), parameters of three different classification methods including Random Forest (RF), K‐Nearest Neighbor (KNN) and Support Vector Machine…”
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On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning by Byrd, Richard H., Chin, Gillian M., Neveitt, Will, Nocedal, Jorge

“…This paper describes how to incorporate sampled curvature information in a Newton-CG method and in a limited memory quasi-Newton method for statistical learning…”
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A wind speed interval prediction system based on multi-objective optimization for machine learning method by Li, Ranran, Jin, Yu

“…•Hybrid framework building on data feature selection method.•Simultaneously the lower and upper bounds of the prediction intervals of future wind speed time series constructed…”
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