Search Results - Restricted stacked autoencoder

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  1. 1

    Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath by Soleymani, Farzan, Paquet, Eric

    ISSN: 0957-4174, 1873-6793
    Published: New York Elsevier Ltd 15.10.2020
    Published in Expert systems with applications (15.10.2020)
    “…•Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy…”
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    Journal Article
  2. 2

    Deep graph convolutional reinforcement learning for financial portfolio management – DeepPocket by Soleymani, Farzan, Paquet, Eric

    ISSN: 0957-4174, 1873-6793
    Published: New York Elsevier Ltd 15.11.2021
    Published in Expert systems with applications (15.11.2021)
    “…•Extracting low-dimensional features using Restricted Stacked Autoencoder.•Interrelation among financial instruments is obtained using a DeepPocket method…”
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    Journal Article
  3. 3

    Cable incipient fault identification using restricted Boltzmann machine and stacked autoencoder by Wang, Ying, Lu, Hong, Xiao, Xianyong, Yang, Xiaomei, Zhang, Wenhai

    ISSN: 1751-8687, 1751-8695
    Published: The Institution of Engineering and Technology 14.04.2020
    “…) and stacked autoencoder (SAE). Firstly, disturbance current waveforms data is effectively compressed by RBM, which can improve analysis efficiency and obtain the shallow features of the data…”
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    Journal Article
  4. 4

    Cancer Diagnosis Using Deep Learning: A Bibliographic Review by Munir, Khushboo, Elahi, Hassan, Ayub, Afsheen, Frezza, Fabrizio, Rizzi, Antonello

    ISSN: 2072-6694, 2072-6694
    Published: Switzerland MDPI AG 23.08.2019
    Published in Cancers (23.08.2019)
    “…In this paper, we first describe the basics of the field of cancer diagnosis, which includes steps of cancer diagnosis followed by the typical classification…”
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    Journal Article
  5. 5

    Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study by Harrou, Fouzi, Dairi, Abdelkader, Dorbane, Abdelhakim, Sun, Ying

    ISSN: 2590-1230, 2590-1230
    Published: Elsevier B.V 01.09.2024
    Published in Results in engineering (01.09.2024)
    “… The method incorporates a Variational Autoencoder (VAE) with a self-attention mechanism applied in both the encoder and decoder…”
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    Journal Article
  6. 6

    Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach by Dairi, Abdelkader, Harrou, Fouzi, Sun, Ying, Khadraoui, Sofiane

    ISSN: 2076-3417, 2076-3417
    Published: MDPI AG 01.12.2020
    Published in Applied sciences (01.12.2020)
    “… This paper intends to provide efficient short-term forecasting of solar power production using Variational AutoEncoder (VAE) model…”
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    Journal Article
  7. 7

    Effect of dimensionality reduction on stock selection with cluster analysis in different market situations by Han, Jingti, Ge, Zhipeng

    ISSN: 0957-4174, 1873-6793
    Published: New York Elsevier Ltd 01.06.2020
    Published in Expert systems with applications (01.06.2020)
    “…–principal component analysis, stacked autoencoder, and stacked restricted Boltzmann machine…”
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    Journal Article
  8. 8

    Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model by Dai, Xiaoai, Cheng, Junying, Guo, Shouheng, Wang, Chengchen, Qu, Ge, Liu, Wenxin, Li, Weile, Lu, Heng, Wang, Youlin, Zeng, Binyang, Peng, Yunjie, Liang, Shuneng

    ISSN: 1026-0226, 1607-887X
    Published: New York Hindawi 28.04.2023
    Published in Discrete dynamics in nature and society (28.04.2023)
    “… Two feature extraction algorithms, the autoencoder (AE) and restricted Boltzmann machine (RBM…”
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    Journal Article
  9. 9

    Learning to Compress Using Deep AutoEncoder by Li, Qing, Chen, Yang

    Published: IEEE 01.09.2019
    “…) stacked of Restricted Boltzmann Machines (RBMs), which form Deep Belief Networks (DBNs). The proposed DAE compression scheme is one variant of the known fixed…”
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    Conference Proceeding
  10. 10

    Intelligent educational systems based on adaptive learning algorithms and multimodal behavior modeling by Li, Yuwei, Lu, Botao

    ISSN: 2376-5992, 2376-5992
    Published: United States PeerJ. Ltd 03.09.2025
    Published in PeerJ. Computer science (03.09.2025)
    “…—including text, images, and interaction logs— via stacked denoising autoencoders and Restricted Boltzmann Machines…”
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    Journal Article
  11. 11
  12. 12

    DeepAM: a heterogeneous deep learning framework for intelligent malware detection by Ye, Yanfang, Chen, Lingwei, Hou, Shifu, Hardy, William, Li, Xin

    ISSN: 0219-1377, 0219-3116
    Published: London Springer London 01.02.2018
    Published in Knowledge and information systems (01.02.2018)
    “…With computers and the Internet being essential in everyday life, malware poses serious and evolving threats to their security, making the detection of malware…”
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    Journal Article
  13. 13

    Unsupervised Detection of Anomalous Behavior in Wireless Devices based on Auto-Encoders by Albasir, A., Hu, Q., Al-tekreeti, M., Naik, K., Naik, N., Kozlowski, A. J., Goel, N.

    ISSN: 2374-9709
    Published: IEEE 01.04.2020
    “… The method consists of two stages: (i) Feature Extraction where stacked Restricted Boltzmann Machine (RBM) AutoEncoders (AE…”
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    Conference Proceeding
  14. 14

    Deep learning algorithms for brain disease detection with magnetic induction tomography by Chen, Ruijuan, Huang, Juan, Song, Yixiang, Li, Bingnan, Wang, Jinhai, Wang, Huiquan

    ISSN: 0094-2405, 2473-4209, 2473-4209
    Published: United States 01.02.2021
    Published in Medical physics (Lancaster) (01.02.2021)
    “…), stacked autoencoder (SAE), and denoising autoencoder (DAE), are used to solve the nonlinear reconstruction problem of MIT, and the reconstruction results of DL networks and back…”
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    Journal Article
  15. 15

    An Improved Data Compression Framework for Wireless Sensor Networks Using Stacked Convolutional Autoencoder (S-CAE) by Kumble, Lithin, Patil, Kiran Kumari

    ISSN: 2661-8907, 2662-995X, 2661-8907
    Published: Singapore Springer Nature Singapore 01.07.2023
    Published in SN computer science (01.07.2023)
    “… We introduce a stacked convolutional RBM auto-encoder (stacked CAE) model for compressing sensor data, which is made up of layers…”
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    Journal Article
  16. 16

    Gaussian Mixture with Max Expectation Guide for Stacked Architecture of Denoising Autoencoder and DRBM for Medical Chest Scans and Disease Identification by Jamjoom, Mona, Mahmoud, Abeer M., Abbas, Safia, Hodhod, Rania

    ISSN: 2079-9292, 2079-9292
    Published: Basel MDPI AG 01.01.2023
    Published in Electronics (Basel) (01.01.2023)
    “…) to extract the regions of interest (ROI), while a convolutional denoising autoencoder (DAE) and deep restricted Boltzmann machine…”
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    Journal Article
  17. 17

    An efficient method for autoencoder‐based collaborative filtering by Wang, Yi‐Lei, Tang, Wen‐Zhe, Yang, Xian‐Jun, Wu, Ying‐Jie, Chen, Fu‐Ji

    ISSN: 1532-0626, 1532-0634
    Published: Hoboken Wiley Subscription Services, Inc 10.12.2019
    Published in Concurrency and computation (10.12.2019)
    “… With rapid development in deep learning, neural network‐based CF models have gained great attention in the recent years, especially autoencoder‐based CF model…”
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    Journal Article
  18. 18

    Performance Comparison of Three Types of Autoencoder Neural Networks by Chun Chet Tan, Eswaran, C.

    ISSN: 2376-1164
    Published: IEEE 01.05.2008
    “…This paper presents a comparison performance on three types of autoencoders, namely, the traditional autoencoder with Restricted Boltzmann Machine (RBM…”
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    Conference Proceeding
  19. 19

    A systematic review on deep learning architectures and applications by Khamparia, Aditya, Singh, Karan Mehtab

    ISSN: 0266-4720, 1468-0394
    Published: Oxford Blackwell Publishing Ltd 01.06.2019
    Published in Expert systems (01.06.2019)
    “…The amount of digital data in the universe is growing at an exponential rate, doubling every 2 years, and changing how we live in the world. The information…”
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    Journal Article
  20. 20

    Reconstruction of handwritten digit images using autoencoder neural networks by Tan, C.C., Eswaran, C.

    ISBN: 9781424416424, 1424416426
    ISSN: 0840-7789
    Published: IEEE 01.05.2008
    “…This paper compares the performances of three types of autoencoder neural networks, namely, the traditional autoencoder with restricted Boltzmann machine (RBM…”
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    Conference Proceeding