Search Results - Restricted stacked autoencoder

Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath

Authors: Soleymani, Farzan Paquet, Eric

Source: Expert Systems with Applications. 156:113456

Subject Terms: blockchain, deep reinforcement learning, Artificial Intelligence, General Engineering, 0202 electrical engineering, electronic engineering, information engineering, portfolio management, online leaning, 02 engineering and technology, settlement risk, Knowmad Institut, Computer Science Applications, restricted stacked autoencoder

File Description: application/pdf

Access URL: https://www.sciencedirect.com/science/article/pii/S0957417420302803
https://www.sciencedirect.com/science/article/abs/pii/S0957417420302803
https://dblp.uni-trier.de/db/journals/eswa/eswa156.html#SoleymaniP20
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002289207461966
https://doi.org/10.1016/j.eswa.2020.113456
https://www.openaccessrepository.it/record/84775

Speech emotion recognition based on a stacked autoencoders optimized by PSO based grass fibrous root optimization.

Authors: Zeng, Chi Li, Jialing Habibi, Abbas

Source: Scientific Reports; 7/18/2025, Vol. 15 Issue 1, p1-16, 16p

Subject Terms: EMOTION recognition, PARTICLE swarm optimization, COMPUTER performance, OPTIMIZATION algorithms, DEEP learning, FEATURE extraction, AUTOENCODERS

Cable incipient fault identification using restricted Boltzmann machine and stacked autoencoder.

Authors: Wang, Ying Lu, Hong Xiao, Xianyong et al.

Source: IET Generation, Transmission & Distribution (Wiley-Blackwell). Apr2020, Vol. 14 Issue 8, p1242-1250. 9p.

Enhanced particle swarm optimization-based hyperparameter optimized stacked autoencoder for credit card fraud detection.

Authors: Abadlia, Houda Smairi, Nadia

Source: International Journal of Data Science & Analytics; Aug2025, Vol. 20 Issue 2, p1239-1253, 15p

Machine learning-based analysis of multi-region bone fracture detection and classification using biomedical images

Authors: Alla M. Elsheikh Azhari A. Elhag

Source: Alexandria Engineering Journal, Vol 128, Iss , Pp 186-199 (2025)

Subject Terms: Bone Fracture Detection, Wild Gibbon Optimization, Weiner Filtering, DenseNet201, Stacked Autoencoder, Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1110016825007033; https://doaj.org/toc/1110-0168

Access URL: https://doaj.org/article/c76d016c267f428c9768e54f322e1e24

Classification of autistic subjects employing modified volume local binary pattern (MVLBP) and stacked Autoencoder (SAE) on functional magnetic resonance imaging (fMRI).

Authors: M., Kaviya Elakkiya Dejey

Source: Multimedia Tools & Applications; Jun2025, Vol. 84 Issue 20, p22161-22186, 26p

Subject Terms: FUNCTIONAL magnetic resonance imaging, INDEPENDENT component analysis, AUTISM spectrum disorders, IMAGE processing, DEEP learning

Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model

Authors: Xiaoai Dai Junying Cheng Shouheng Guo et al.

Source: Discrete Dynamics in Nature and Society, Vol 2023 (2023)

Subject Terms: Mathematics, QA1-939

File Description: electronic resource

Relation: https://doaj.org/toc/1607-887X

Access URL: https://doaj.org/article/71c0bb7c7e5e435bbe38d9f526122872

Type 2 Diabetes Data Classification Using an Attention-based Stacked Autoencoder and TabNet Hybrid Model.

Authors: Aleesa, Rula Sami Al-bermani, Noora kadhim Ismael, Hayder A.

Source: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 3, p761-772, 12p

Subject Terms: CLINICAL decision support systems, TYPE 2 diabetes, MACHINE learning, DISEASE risk factors, RECEIVER operating characteristic curves, FEATURE extraction

A study on the similarities of Deep Belief Networks and Stacked Autoencoders

Authors: de Giorgio, Andrea

Subject Terms: Deep Learning, Restricted Boltzmann Machine, Stacked Autoencoder, Autoencoder, Depp Belief Network, Machine Learning, Computer Science, F-Mapping, Electrical Engineering, Electronic Engineering, Information Engineering, Elektroteknik och elektronik

File Description: application/pdf

Availability: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174341

Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model.

Authors: Dai, Xiaoai Cheng, Junying Guo, Shouheng et al.

Source: Discrete Dynamics in Nature & Society; 4/28/2023, p1-20, 20p

Subject Terms: DEEP learning, IMAGE recognition (Computer vision), REMOTE-sensing images, BOLTZMANN machine, REMOTE sensing, FEATURE extraction, ELECTRONIC data processing

Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks.

Authors: Prasad, Kashi Sai Lydia, E. Laxmi Rajesh, M. V. et al.

Source: Scientific Reports; 12/28/2024, Vol. 14 Issue 1, p1-23, 23p

Subject Terms: OPTIMIZATION algorithms, COMPUTER input design, ARTIFICIAL intelligence, CYBERTERRORISM, DATABASES

Performance enhancement in hybrid SDN using advanced deep learning with multi‐objective optimization frameworks under heterogeneous environments.

Authors: Bishla, Deepak Kumar, Brijesh

Source: International Journal of Communication Systems; 2/1/2025, Vol. 38 Issue 3, p1-18, 18p

Subject Terms: SOFTWARE-defined networking, AUTOENCODERS, ZEBRAS, TOPOLOGY

An improved hybrid semi-stacked autoencoder for item-features of recommendation system (iHSARS).

Authors: Al-Sbou, Ahed Mleih Abd Rahim, Noor Hafhizah

Source: Indonesian Journal of Electrical Engineering & Computer Science; Apr2023, Vol. 30 Issue 1, p481-490, 10p

Subject Terms: RECOMMENDER systems, STANDARD deviations, AUTOENCODERS, INFORMATION overload, INFORMATION resources, DEEP learning

Dynamic Depth Learning in Stacked AutoEncoders.

Authors: Alfayez, Sarah Bchir, Ouiem Ben Ismail, Mohamed Maher

Source: Applied Sciences (2076-3417); Oct2023, Vol. 13 Issue 19, p10994, 22p

Subject Terms: DEEP learning, TOPOLOGY

Enhanced Face Recognition in Crowded Environments with 2D/3D Features and Parallel Hybrid CNN-RNN Architecture with Stacked Auto-Encoder.

Authors: Elloumi, Samir Bahroun, Sahbi Yahia, Sadok Ben et al.

Source: Big Data & Cognitive Computing; Aug2025, Vol. 9 Issue 8, p191, 26p

Subject Terms: DEEP learning, FEATURE extraction, IMAGE processing, ELECTRONIC surveillance, FACE perception, PARALLEL processing

Deep graph convolutional reinforcement learning for financial portfolio management – DeepPocket

Authors: Soleymani, Farzan Paquet, Eric

Source: Expert Systems with Applications. 182:115127

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, deep reinforcement learning, online learning, 05 social sciences, Computational Finance (q-fin.CP), 02 engineering and technology, Machine Learning (cs.LG), Computational Engineering, Finance, and Science (cs.CE), FOS: Economics and business, Quantitative Finance - Computational Finance, graph convolutional network, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, portfolio management, actor-critic, Computer Science - Computational Engineering, Finance, and Science, restricted stacked autoencoder

Access URL: http://arxiv.org/pdf/2105.08664
http://arxiv.org/abs/2105.08664
https://arxiv.org/abs/2105.08664
https://dblp.uni-trier.de/db/journals/corr/corr2105.html#abs-2105-08664
https://doi.org/10.1016/j.eswa.2021.115127
https://europepmc.org/article/PPR/PPR343354
https://arxiv.org/pdf/2105.08664.pdf
https://www.sciencedirect.com/science/article/abs/pii/S0957417421005686

Plastic Extrusion Process Optimization by Inversion of Stacked Autoencoder Classification Machines.

Authors: Burr, Julia Sarishvili, Alex Just, Daniel et al.

Source: Chemie Ingenieur Technik (CIT); Oct2023, Vol. 95 Issue 10, p1555-1562, 8p

Subject Terms: PLASTIC extrusion, PROCESS optimization, DIGITAL twin, ENERGY consumption, EXTRUSION process

A study on the similarities of Deep Belief Networks and Stacked Autoencoders

Authors: Giorgio, Andrea De

Subject Terms: Machine Learning, Deep Learning, Stacked Autoencoder, Restricted Boltzmann Machine, Computer Science, Restricted Boltzmann Machines, Stacked Autoencoders, Stacked Denoising Autoencoders, Autoencoder, Electrical Engineering, Electronic Engineering, Information Engineering, Elektroteknik och elektronik, F-Mapping, Depp Belief Network

File Description: application/pdf

Access URL: http://www.diva-portal.org/smash/record.jsf?pid=diva2:859006
https://zenodo.org/record/4104691
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174341

Intelligent Fault Prognosis Method Based on Stacked Autoencoder and Continuous Deep Belief Network.

Authors: Zhang, Chao Zhang, Yibin Huang, Qixuan et al.

Source: Actuators; Mar2023, Vol. 12 Issue 3, p117, 22p

Subject Terms: STOCK index futures, CONDITION-based maintenance, FAULT diagnosis, MOVING average process, STATISTICAL smoothing, TIME series analysis, DEEP learning

Stacked autoencoder with novel integrated activation functions for the diagnosis of autism spectrum disorder.

Authors: M, Kaviya Elakkiya Dejey

Source: Neural Computing & Applications; Aug2023, Vol. 35 Issue 23, p17043-17075, 33p

Subject Terms: DEEP learning, AUTISM spectrum disorders, COMPUTER-aided diagnosis, FUNCTIONAL magnetic resonance imaging, INDEPENDENT component analysis, PRINCIPAL components analysis

Company/Entity: UNIVERSITY of California, Los Angeles