Výsledky vyhledávání - "Restricted stacked autoencoder"

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

Autoři: Soleymani, Farzan Paquet, Eric

Zdroj: Expert Systems with Applications. 156:113456

Témata: 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

Popis souboru: application/pdf

Přístupová URL adresa: 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

Deep graph convolutional reinforcement learning for financial portfolio management – DeepPocket

Autoři: Soleymani, Farzan Paquet, Eric

Zdroj: Expert Systems with Applications. 182:115127

Témata: 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

Přístupová URL adresa: 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

Robot motion skill learning method based on focused reward transformer.

Autoři: Nan, Borui Zheng, Xinyi Gong, Wanru a další

Zdroj: Scientific Reports; 11/13/2025, Vol. 15 Issue 1, p1-12, 12p

MCN portfolio: An efficient portfolio prediction and selection model using multiserial cascaded network with hybrid meta-heuristic optimization algorithm.

Autoři: Sharma, Meeta Sharma, Pankaj Kumar Vijayvergia, Hemant Kumar a další

Zdroj: Network: Computation in Neural Systems; Aug2025, Vol. 36 Issue 3, p818-854, 37p

Adaptive Portfolio Optimization with Multi-Agent Deep Reinforcement Learning and Short-Term Performance Analysis.

Autoři: Movassaghpour, Shahin Sharbaf Kargar, Masoud Bayani, Ali a další

Zdroj: International Journal of Information & Communication Technology Research (2251-6107); 2025, Vol. 17 Issue 3, p58-69, 12p

Témata: PORTFOLIO management (Investments), REINFORCEMENT learning, COMPUTER performance, FINANCIAL performance, MODEL validation, MARKET sentiment, DYNAMICAL systems

A Computational Methodology Based on Maximum Overlap Discrete Wavelet Transform and Autoencoders for Early Prediction of Sudden Cardiac Death.

Autoři: Centeno-Bautista, Manuel A. Perez-Sanchez, Andrea V. Amezquita-Sanchez, Juan P. a další

Zdroj: Computation; Jun2025, Vol. 13 Issue 6, p130, 22p

Témata: CARDIAC arrest, COMPUTATIONAL biology, SIGNAL processing, CARDIOVASCULAR diseases, WORLD health, DEEP learning

Risk-Adjusted Deep Reinforcement Learning for Portfolio Optimization: A Multi-reward Approach.

Autoři: Choudhary, Himanshu Orra, Arishi Sahoo, Kartik a další

Zdroj: International Journal of Computational Intelligence Systems; 5/26/2025, Vol. 18 Issue 1, p1-19, 19p

A taxonomy of literature reviews and experimental study of deepreinforcement learning in portfolio management: A taxonomy of literature reviews and experimental study: M. Rezaei and H. Nezamabadi-Pour.

Autoři: Rezaei, Mohadese Nezamabadi-Pour, Hossein

Zdroj: Artificial Intelligence Review; Mar2025, Vol. 58 Issue 3, p1-46, 46p

A Systematic Approach to Portfolio Optimization: A Comparative Study of Reinforcement Learning Agents, Market Signals, and Investment Horizons.

Autoři: Espiga-Fernández, Francisco García-Sánchez, Álvaro Ordieres-Meré, Joaquín

Zdroj: Algorithms; Dec2024, Vol. 17 Issue 12, p570, 37p

Témata: DEEP reinforcement learning, REINFORCEMENT learning, PORTFOLIO management (Investments), MACHINE learning, STANDARD & Poor's 500 Index

Deep Learning in Finance: A Survey of Applications and Techniques.

Autoři: Mienye, Ebikella Jere, Nobert Obaido, George a další

Zdroj: AI; Dec2024, Vol. 5 Issue 4, p2066-2091, 26p

Témata: REINFORCEMENT learning, DEEP reinforcement learning, LONG short-term memory, GENERATIVE adversarial networks, MACHINE learning, DEEP learning

Ensemble of temporal Transformers for financial time series.

Autoři: Olorunnimbe, Kenniy Viktor, Herna

Zdroj: Journal of Intelligent Information Systems; Aug2024, Vol. 62 Issue 4, p1087-1111, 25p

Témata: MACHINE learning, DOW Jones industrial average, TRANSFORMER models, DEEP learning, BUSINESS forecasting

Towards efficient similarity embedded temporal Transformers via extended timeframe analysis.

Autoři: Olorunnimbe, Kenniy Viktor, Herna

Zdroj: Complex & Intelligent Systems; Aug2024, Vol. 10 Issue 4, p4793-4815, 23p

Témata: TRANSFORMER models, FINANCIAL markets, TIME series analysis, TIME measurements, MARKET timing, DEEP learning, BOX-Jenkins forecasting

Blockchain-Based Lean Supply Chain: A Simulation Approach.

Autoři: Morelli, Daniel Alexandre Ignácio, Paulo Sérgio de Arruda Zanutim, Nicholas Leonardi

Zdroj: International Journal of Innovation & Technology Management; Aug2024, Vol. 21 Issue 5, p1-44, 44p

Témata: BLOCKCHAINS, SUPPLY chains, SUPPLY chain management, EVIDENCE gaps, LEAN management, 5G networks

Enhancing the chimp optimization algorithm to evolve deep LSTMs for accounting profit prediction using adaptive pair reinforced technique.

Autoři: Yang, Chengchen Wu, Tong Zeng, Lingzhuo

Zdroj: Evolving Systems; Aug2024, Vol. 15 Issue 4, p1159-1178, 20p

Portfolio Optimization using Artificial Intelligence: a systematic literature review.

Autoři: Carvalho Santos, Gustavo Barboza, Flavio Paschoarelli Veiga, Antônio Cláudio a další

Zdroj: Exacta; jul-set2024, Vol. 22 Issue 3, p766-787, 22p

Témata: ARTIFICIAL intelligence, RISK-return relationships, MACHINE learning, REINFORCEMENT learning

Causal Inference and Prefix Prompt Engineering Based on Text Generation Models for Financial Argument Analysis.

Autoři: Ding, Fei Kang, Xin Wang, Linhuang a další

Zdroj: Electronics (2079-9292); May2024, Vol. 13 Issue 9, p1746, 15p

Témata: CAUSAL inference, CORPORATE finance, NATURAL language processing, SUFFIXES & prefixes (Grammar), CHATGPT

Multi-factor stock trading strategy based on DQN with multi-BiGRU and multi-head ProbSparse self-attention.

Autoři: Liu, Wenjie Gu, Yuchen Ge, Yebo

Zdroj: Applied Intelligence; Apr2024, Vol. 54 Issue 7, p5417-5440, 24p

Témata: STOCKS (Finance), DEEP reinforcement learning, INVESTORS, REINFORCEMENT learning, FINANCIAL markets, CRYPTOCURRENCIES

Deep Learning for Financial Time Series Prediction: A State-of-the-Art Review of Standalone and Hybrid Models.

Autoři: Weisi Chen Hussain, Walayat Cauteruccio, Francesco a další

Zdroj: Computer Modeling in Engineering & Sciences (CMES); 2024, Vol. 139 Issue 1, p187-224, 38p

RDMAA: Robust Defense Model against Adversarial Attacks in Deep Learning for Cancer Diagnosis.

Autoři: El-Aziz, Atrab A. Abd El-Khoribi, Reda A. Khalifa, Nour Eldeen

Zdroj: International Journal of Computing & Digital Systems; Feb2024, Vol. 15 Issue 1, p1273-1287, 15p

Témata: DEEP learning, CANCER diagnosis, CONVOLUTIONAL neural networks, MAGNETIC resonance imaging, WEIGHT training

An integrative extraction approach for index-tracking portfolio construction and forecasting under a deep learning framework.

Autoři: Wang, Yu-Ju Wu, Liang-Hong Wu, Liang-Chuan

Zdroj: Journal of Supercomputing; Jan2024, Vol. 80 Issue 2, p2047-2066, 20p

Témata: DEEP learning, PORTFOLIO management (Investments), ARTIFICIAL neural networks, STOCHASTIC dominance, SUPERVISED learning, INVESTORS