Suchergebnisse - Restricted stacked autoencoder

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

“… •Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy …”
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Deep graph convolutional reinforcement learning for financial portfolio management – DeepPocket von Soleymani, Farzan, Paquet, Eric

“… •Extracting low-dimensional features using Restricted Stacked Autoencoder.•Interrelation among financial instruments is obtained using a DeepPocket method …”
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Cable incipient fault identification using restricted Boltzmann machine and stacked autoencoder von Wang, Ying, Lu, Hong, Xiao, Xianyong, Yang, Xiaomei, Zhang, Wenhai

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

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

“… The method incorporates a Variational Autoencoder (VAE) with a self-attention mechanism applied in both the encoder and decoder …”
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Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach von Dairi, Abdelkader, Harrou, Fouzi, Sun, Ying, Khadraoui, Sofiane

“… This paper intends to provide efficient short-term forecasting of solar power production using Variational AutoEncoder (VAE) model …”
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Effect of dimensionality reduction on stock selection with cluster analysis in different market situations von Han, Jingti, Ge, Zhipeng

“… –principal component analysis, stacked autoencoder, and stacked restricted Boltzmann machine …”
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Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model von Dai, Xiaoai, Cheng, Junying, Guo, Shouheng, Wang, Chengchen, Qu, Ge, Liu, Wenxin, Li, Weile, Lu, Heng, Wang, Youlin, Zeng, Binyang, Peng, Yunjie, Liang, Shuneng

“… Two feature extraction algorithms, the autoencoder (AE) and restricted Boltzmann machine (RBM …”
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Learning to Compress Using Deep AutoEncoder von Li, Qing, Chen, Yang

“… ) 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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Intelligent educational systems based on adaptive learning algorithms and multimodal behavior modeling von Li, Yuwei, Lu, Botao

“… —including text, images, and interaction logs— via stacked denoising autoencoders and Restricted Boltzmann Machines …”
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Heart Failure diagnosis based on deep learning techniques von Papadopoulos, Theofilos G., Plati, Daphni, Tripoliti, Evanthia E., Goletsis, Yorgos, Naka, Katerina K., Rammos, Aidonis, Bechlioulis, Aris, Watson, Chris, McDonald, Kenneth, Ledwidge, Mark, Pharithi, Rebabonye, Gallagher, Joseph, Fotiadis, Dimitrios I.

“… Seven deep learning architectures are implemented, where stacked Restricted Boltzman Machines (RBMs …”
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DeepAM: a heterogeneous deep learning framework for intelligent malware detection von Ye, Yanfang, Chen, Lingwei, Hou, Shifu, Hardy, William, Li, Xin

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

“… The method consists of two stages: (i) Feature Extraction where stacked Restricted Boltzmann Machine (RBM) AutoEncoders (AE …”
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Deep learning algorithms for brain disease detection with magnetic induction tomography von Chen, Ruijuan, Huang, Juan, Song, Yixiang, Li, Bingnan, Wang, Jinhai, Wang, Huiquan

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

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

“… ) to extract the regions of interest (ROI), while a convolutional denoising autoencoder (DAE) and deep restricted Boltzmann machine …”
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An efficient method for autoencoder‐based collaborative filtering von Wang, Yi‐Lei, Tang, Wen‐Zhe, Yang, Xian‐Jun, Wu, Ying‐Jie, Chen, Fu‐Ji

“… 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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Performance Comparison of Three Types of Autoencoder Neural Networks von Chun Chet Tan, Eswaran, C.

“… This paper presents a comparison performance on three types of autoencoders, namely, the traditional autoencoder with Restricted Boltzmann Machine (RBM …”
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A systematic review on deep learning architectures and applications von Khamparia, Aditya, Singh, Karan Mehtab

“… 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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Reconstruction of handwritten digit images using autoencoder neural networks von Tan, C.C., Eswaran, C.

“… 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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