Suchergebnisse - "Parallel machine learning algorithm"

High-performance medical data processing technology based on distributed parallel machine learning algorithm von Liu, Ji, Liang, Xiao, Ruan, Wenxi, Zhang, Bo

“… The aim is to improve the efficiency of medical data processing and establish a sound medical data management system. To apply distributed parallel …”
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Parallel Machine Learning Algorithm Using Fine-Grained-Mode Spark on a Mesos Big Data Cloud Computing Software Framework for Mobile Robotic Intelligent Fault Recognition von Xian, Guangming

“… To improve the efficiency of intelligent fault classification of mobile robotic roller bearings, this paper proposes a parallel machine learning algorithm using fine-grained-mode Spark on a Mesos big …”
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Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing von Djafri, Laouni

“… PurposeThis work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other …”
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Hadoop based Parallel Machine Learning Algorithms for Intrusion Detection System von Eswaran, Malathi, Balasubramanie, P., Jotheeswari, M.

“… Web use and digitized information are getting expanded each day. The measure of information created is likewise getting expanded. On the opposite side, the …”
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Incremental and Parallel Machine Learning Algorithms With Automated Learning Rate Adjustments von Hishinuma, Kazuhiro, Iiduka, Hideaki

“… The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates …”
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TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests von Carrasco Kind, Matias, Brunner, Robert J.

“… In this paper, we present a new, publicly available, parallel, machine learning algorithm that generates photometric redshift PDFs by using prediction trees and random forest techniques, which we have named TPZ …”
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Performance and Energy Consumption of Parallel Machine Learning Algorithms von Wu, Xidong, Preston Brazzle, Cahoon, Stephen

“… Machine learning models have achieved remarkable success in various real-world applications such as data science, computer vision, and natural language …”
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Incremental and Parallel Machine Learning Algorithms with Automated Learning Rate Adjustments von Hishinuma, Kazuhiro, Iiduka, Hideaki

“… The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates …”
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Scalable and parallel machine learning algorithms for statistical data mining - Practice & experience von Riedel, M., Goetz, M., Richerzhagen, M., Glock, P., Bodenstein, C., Memon, A. S., Memon, M. S.

“… Many scientific datasets (e.g. earth sciences, medical sciences, etc.) increase with respect to their volume or in terms of their dimensions due to the ever …”
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Analysis of visible–near infrared spectral characteristics for water layer management of rice based on the big data platform von Xia, Ji’An, Zhang, WeiXin, Zhang, WenYu, Mu, WenTao, Xu, RongWang, Yuan, WangHao, Ge, DaoKuo, Zhang, Qian, Ge, SiJun, Cao, HongXin

“… The objective of this study was to evaluate the potential of big data technology for spectral feature extraction rice plants under different water management …”
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Fast parallel machine learning algorithms for large datasets using graphic processing unit von Li, Qi

“… This dissertation deals with developing parallel processing algorithms for Graphic Processing Unit (GPU) in order to solve machine learning problems for large …”
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Cloud-based machine learning for predictive analytics: Tool wear prediction in milling von Dazhong Wu, Jennings, Connor, Terpenny, Janis, Kumara, Soundar

“… The proliferation of real-time monitoring systems and the advent of Industrial Internet of Things (IIoT) over the past few years necessitates the development …”
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Machine Learning Applications for Weather and Climate Modeling von Arcomano, Troy Joseph

“… This study investigates the applications of machine learning (ML) to weather and climate modeling. We first show the potential for data-driven weather …”
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TPZ : Photometric redshift PDFs and ancillary information by using prediction trees and random forests von M Carrasco Kind, Brunner, R J

“… In this paper, we present a new, publicly available, parallel, machine learning algorithm that generates photometric redshift PDFs by using prediction trees and random forest techniques, which we have named TPZ …”
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The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters von Cheng, Daning, Zhang, Hanping, Xia, Fen, Li, Shigang, Zhang, Yunquan

“… but there are very few research efforts explaining the reasons in essence. In this paper, we propose that the sample difference in dataset plays a more prominent role in parallel machine learning algorithm scalability …”
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Predicting atomic-level reaction mechanisms for SN2 reactions via machine learning von Meng, Fanbin, Li, Yan, Wang, Dunyou

“… Identifying atomic-level reaction mechanisms is an essential step in chemistry. In this study, we develop a joint-voting model based on three parallel machine …”
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Machine Learning Analysis Using the Black Oil Model and Parallel Algorithms in Oil Recovery Forecasting von Matkerim, Bazargul, Mukhanbet, Aksultan, Kassymbek, Nurislam, Daribayev, Beimbet, Mustafin, Maksat, Imankulov, Timur

“… The accurate forecasting of oil recovery factors is crucial for the effective management and optimization of oil production processes. This study explores the …”
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A Stand-Alone Polarimetric Acquisition System for Producing a Long-Term Skylight Dataset von Poughon, Leo, Aubry, Vincent, Monnoyer, Jocelyn, Viollet, Stephane, Serres, Julien R

“… Skylight-based orientation sensors can be simulated on the basis of physical models. In parallel, machine learning algorithms require a large amount of data to be trained …”
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Bayesian classifier applications of airborne hyperspectral imagery processing for forested areas von Kozoderov, Vladimir, Kondranin, Timofei, Dmitriev, Egor, Kamentsev, Vladimir

“… Main attention is paid to Bayesian classifier that can be used to realize the processing procedures based on parallel machine-learning algorithms and high-productive computers …”
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Why Dataset Properties Bound the Scalability of Parallel Machine Learning Training Algorithms von Cheng, Daning, Li, Shigang, Zhang, Hanping, Xia, Fen, Zhang, Yunquan

“… In this paper, we demonstrate that the sample difference in the dataset plays a prominent role in the scalability of parallel machine learning algorithms …”
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