Výsledky vyhledávání - Batch gradient learning algorithm

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  1. 1

    Convergence of batch gradient learning algorithm with smoothing L1/2 regularization for Sigma–Pi–Sigma neural networks Autor Liu, Yan, Li, Zhengxue, Yang, Dakun, Mohamed, Kh.Sh, Wang, Jing, Wu, Wei

    ISSN: 0925-2312, 1872-8286
    Vydáno: Elsevier B.V 03.03.2015
    Vydáno v Neurocomputing (Amsterdam) (03.03.2015)
    “…–Sigma neural networks. Compared with conventional gradient learning algorithm, this method produces sparser weights and simpler structure, and it improves the learning efficiency…”
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    Deterministic convergence of complex mini-batch gradient learning algorithm for fully complex-valued neural networks Autor Zhang, Huisheng, Zhang, Ying, Zhu, Shuai, Xu, Dongpo

    ISSN: 0925-2312, 1872-8286
    Vydáno: Elsevier B.V 24.09.2020
    Vydáno v Neurocomputing (Amsterdam) (24.09.2020)
    “…This paper investigates the fully complex mini-batch gradient algorithm for training complex-valued neural networks…”
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    Batch Gradient Learning Algorithm with Smoothing L1 Regularization for Feedforward Neural Networks Autor Mohamed, Khidir Shaib

    ISSN: 2073-431X, 2073-431X
    Vydáno: Basel MDPI AG 01.01.2023
    Vydáno v Computers (Basel) (01.01.2023)
    “… In this paper, we propose a batch gradient learning algorithm with smoothing L1 regularization (BGSL1…”
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  5. 5

    Batch Gradient Learning Algorithm with Smoothing Regularization for Feedforward Neural Networks Autor Khidir Shaib Mohamed

    ISSN: 2073-431X
    Vydáno: MDPI AG 01.12.2022
    Vydáno v Computers (Basel) (01.12.2022)
    “… In this paper, we propose a batch gradient learning algorithm with smoothing L1 regularization (BGS L1…”
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  6. 6

    Strong Convergence Analysis of Batch Gradient-Based Learning Algorithm for Training Pi-Sigma Network Based on TSK Fuzzy Models Autor Liu, Yan, Yang, Dakun, Nan, Nan, Guo, Li, Zhang, Jianjun

    ISSN: 1370-4621, 1573-773X
    Vydáno: New York Springer US 01.06.2016
    Vydáno v Neural processing letters (01.06.2016)
    “… The aim of this paper is to present a gradient-based learning method for Pi-Sigma network to train TSK fuzzy inference system…”
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  7. 7

    Convergence analysis of the batch gradient-based neuro-fuzzy learning algorithm with smoothing L1/2 regularization for the first-order Takagi–Sugeno system Autor Liu, Yan, Yang, Dakun

    ISSN: 0165-0114, 1872-6801
    Vydáno: Elsevier B.V 15.07.2017
    Vydáno v Fuzzy sets and systems (15.07.2017)
    “… The neuro-fuzzy learning algorithm involves two tasks: generating comparable sparse networks and training the parameters…”
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  8. 8

    A Batch Variable Learning Rate Gradient Descent Algorithm With the Smoothing L1/2 Regularization for Takagi-Sugeno Models Autor Lu, Yunlong, Li, Wenyu, Wang, Hongwei

    ISSN: 2169-3536
    Vydáno: IEEE 2020
    Vydáno v IEEE access (2020)
    “…A batch variable learning rate gradient descent algorithm is proposed to efficiently train a neuro-fuzzy network of zero-order Takagi-Sugeno inference systems…”
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    A Batch Variable Learning Rate Gradient Descent Algorithm With the Smoothing L 1/2 Regularization for Takagi-Sugeno Models Autor Lu, Yunlong, Li, Wenyu, Wang, Hongwei

    ISSN: 2169-3536, 2169-3536
    Vydáno: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020
    Vydáno v IEEE access (2020)
    “…A batch variable learning rate gradient descent algorithm is proposed to efficiently train a neuro-fuzzy network of zero-order Takagi-Sugeno inference systems…”
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    Network revenue management with online inverse batch gradient descent method Autor Chen, Yiwei, Shi, Cong

    ISSN: 1059-1478, 1937-5956
    Vydáno: Los Angeles, CA SAGE Publications 01.07.2023
    Vydáno v Production and operations management (01.07.2023)
    “…' prices but is concave in products' market shares (or price‐controlled demand rates). This creates challenges in adopting any stochastic gradient descent…”
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    Trustworthy Network Anomaly Detection Based on an Adaptive Learning Rate and Momentum in IIoT Autor Yan, Xiaodan, Xu, Yang, Xing, Xiaofei, Cui, Baojiang, Guo, Zihao, Guo, Taibiao

    ISSN: 1551-3203, 1941-0050
    Vydáno: Piscataway IEEE 01.09.2020
    “… and trustworthiness of IIoT devices has become an urgent problem to solve. In this article, we design a new hinge classification algorithm based on mini-batch gradient descent with an adaptive learning rate and momentum (HCA-MBGDALRM…”
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    Big data dimensionality reduction-based supervised machine learning algorithms for NASH diagnosis Autor Tutsoy, Onder, Ozturk, Huseyin Ali, Sumbul, Hilmi Erdem

    ISSN: 1471-2105, 1471-2105
    Vydáno: London BioMed Central 21.10.2025
    Vydáno v BMC bioinformatics (21.10.2025)
    “… Optimization with Artificial Neural Networks (PSO-ANN) machine learning algorithm. Then, a gradient based Batch Least Squares (BLS…”
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    A learning algorithm with a gradient normalization and a learning rate adaptation for the mini-batch type learning Autor Ito, Daiki, Okamoto, Takashi, Koakutsu, Seiichi

    Vydáno: The Society of Instrument and Control Engineers - SICE 01.09.2017
    “… The learning algorithms with gradient normalization mechanisms have been investigated, and their effectiveness has been shown…”
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  14. 14

    Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts Autor Zhou, Yanlai, Chang, Fi-John, Chang, Li-Chiu, Kao, I-Feng, Wang, Yi-Shin

    ISSN: 0959-6526, 1879-1786
    Vydáno: Elsevier Ltd 01.02.2019
    Vydáno v Journal of cleaner production (01.02.2019)
    “…) neural network model that were incorporated with three deep learning algorithms (i.e., mini-batch gradient descent, dropout neuron and L2 regularization…”
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    Adaptive stochastic conjugate gradient for machine learning Autor Yang, Zhuang

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 15.11.2022
    Vydáno v Expert systems with applications (15.11.2022)
    “…) algorithms have been widely used in machine learning. This paper considers conjugate gradient in the mini-batch setting…”
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    A Static Security Region Analysis of New Power Systems Based on Improved Stochastic–Batch Gradient Pile Descent Autor Wu, Jiahui, Zhou, Yide, Wang, Haiyun, Wang, Weiqing

    ISSN: 2076-3417, 2076-3417
    Vydáno: Basel MDPI AG 01.05.2024
    Vydáno v Applied sciences (01.05.2024)
    “… To address the slow training speed of traditional deep learning algorithms using batch gradient descent (BGD…”
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    A new lightweight deep neural network for surface scratch detection Autor Li, Wei, Zhang, Liangchi, Wu, Chuhan, Cui, Zhenxiang, Niu, Chao

    ISSN: 0268-3768, 1433-3015
    Vydáno: London Springer London 01.11.2022
    “… To this end, a large surface scratch dataset obtained from cylinder-on-flat sliding tests was used to train the WearNet with appropriate training parameters such as learning rate, gradient algorithm and mini-batch size…”
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    A Fast Adaptive Online Gradient Descent Algorithm in Over-Parameterized Neural Networks Autor Yang, Anni, Li, Dequan, Li, Guangxiang

    ISSN: 1370-4621, 1573-773X
    Vydáno: New York Springer US 01.08.2023
    Vydáno v Neural processing letters (01.08.2023)
    “… Although many first-order adaptive gradient algorithms (e.g., Adam, AdaGrad) have been proposed to adjust the learning rate, they are vulnerable to the initial learning…”
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    Reinforcement learning based optimal control of batch processes using Monte-Carlo deep deterministic policy gradient with phase segmentation Autor Yoo, Haeun, Kim, Boeun, Kim, Jong Woo, Lee, Jay H.

    ISSN: 0098-1354, 1873-4375
    Vydáno: Elsevier Ltd 04.01.2021
    Vydáno v Computers & chemical engineering (04.01.2021)
    “…•DDPG algorithm is modified with Monte-Carlo learning for stable agent training.•Suggested algorithm is applied to a batch polymerization process control problem…”
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    Comparison of Stochastic Steepest Gradient Descent and Extended Kalman Filter as ARMA-FNN Learning Algorithms for Data-Driven System Identification of Batch Distillation Column Autor Nasution, Muhammad Alifsyah Putra, Mahayana, Dimitri, Rusmin, Pranoto Hidaya, Zidni, Hasan

    ISSN: 2470-640X
    Vydáno: IEEE 02.10.2023
    “… The plant used in this study is a batch-type distillation column system located in the ITB Honeywell Control Systems Laboratory, capable of separating binary mixtures of ethanol and water…”
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