Výsledky vyhľadávania - ML: Reinforcement Learning Algorithms*

Software defined networking for autonomous and secure optical networks

Autori: Hernández Chulde, Carlos Efrén

Prispievatelia: University/Department: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions

Thesis Advisors: Casellas Regí, Ramon, Martínez Rivera, Ricardo Víctor, Comellas Colomé, Jaume

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Routing and Spectrum Assignment, Elastic Optical Networks, Deep Reinforcement Learning, Software Defined Networking, Network Functions Virtualization, Virtual Network Functions, VNF placement, Quantum Key Distribution, Continuous Variable Quantum Key Distribution, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació, 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/694378
https://dx.doi.org/10.5821/dissertation-2117-428870

An overview of artificial intelligence and machine learning in shoulder surgery.

Autori: Cho, Sung-Hyun Kim, Yang-Soo

Zdroj: Clinics in Shoulder & Elbow; Jun2025, Vol. 28 Issue 2, p242-250, 9p

Predmety: MACHINE learning, FEDERATED learning, ENSEMBLE learning, ARTIFICIAL intelligence, REINFORCEMENT learning

Zero-touch service orchestration in 5G and beyond mobile networks

Autori: Dalgkitsis, Anestis

Prispievatelia: University/Department: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions

Thesis Advisors: Verikoukis, Christos, Ramantas, Konstantinos, Alonso Zárate, Luis Gonzaga

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Zero-touch Management & Orchestration (ZSM), Machine Learning (ML), Reinforcement Learning (RL), Network Function Virtualization (NFV), Network Slicing (NS), Software Defined Networking (SDN), Ultra-Reliable Low Latency Communications (URLLC), Gestió i orquestració de zero toc (ZSM), Aprenentatge automàtic (ML), Aprenentatge de reforç (RL), Virtualització de funcions de xarxa (NFV), Xarxa definida per programari (SDN), Baixa latència ultra fiable Comunicacions (URLLC), Gestión y orquestación sin contacto (ZSM), Aprendizaje automático (ML), Aprendizaje por Refuerzo (RL), Virtualización de funciones de red (NFV), Redes definidas por software (SDN), Baja latencia ultraconfiable Comunicaciones (URLLC), Àrees temàtiques de la UPC::Enginyeria de la telecomunicació

Time: 621.3

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/690299
https://dx.doi.org/10.5821/dissertation-2117-404663

Machine learning algorithms in intermittent demand forecasting: a review.

Autori: Giannopoulos, Panagiotis G. Dasaklis, Thomas K. Tsantilis, Ioannis a ďalší

Zdroj: International Journal of Production Research. Oct2025, p1-43. 43p. 9 Illustrations.

Predmety: *TIME series analysis, *STANDARDIZATION, MACHINE learning, DEMAND forecasting, FEATURE selection, TRANSFER of training, INDEPENDENT variables

Simulated Autonomous Driving Using Reinforcement Learning: A Comparative Study on Unity's ML-Agents Framework.

Autori: Savid, Yusef Mahmoudi, Reza Maskeliūnas, Rytis a ďalší

Zdroj: Information. May2023, Vol. 14 Issue 5, p290. 22p.

Predmety: *Intelligent agents, *Artificial intelligence, Reinforcement learning, Autonomous vehicles, Optimization algorithms, Horse racetracks

On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure

Autori: Russo, Alessio Proutiere, Alexandre

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence. :9658-9667

Predmety: ML: Representation Learning, ML: Online Learning & Bandits, ML: Reinforcement Learning Algorithms, ML: Reinforcement Learning Theory, Mathematical Statistics, Matematisk statistik, Electrical Engineering, Elektro- och systemteknik, Datalogi, Computer Science

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-333761
https://doi.org/10.1609/aaai.v37i8.26155

Development of Advance Machine Learning (ML) Strategies for Enhanced Mobile Robot Control.

Autori: Prashanthi, Valishetti Anitha, Akula devi, L. Madhuri a ďalší

Zdroj: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 2, p2369-2391, 23p

Predmety: ARTIFICIAL neural networks, REINFORCEMENT learning, MACHINE learning, DEEP reinforcement learning, ROBOT control systems

Exploring reinforcement learning in process control: a comprehensive survey.

Autori: Rajasekhar, N. Radhakrishnan, T.K. Samsudeen, N.

Zdroj: International Journal of Systems Science. Oct2025, Vol. 56 Issue 14, p3528-3557. 30p.

Predmety: *PROCESS control systems, *DECISION making, *ALGORITHMS, *INDUSTRIAL applications, REINFORCEMENT learning, MACHINE learning, DEEP learning

Enabling knowledge-defined networks : deep reinforcement learning, graph neural networks and network analytics

Autori: Suárez-Varela Macià, José Rafael

Prispievatelia: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Barlet Ros, Pere, Cabellos Aparicio, Alberto

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Àrees temàtiques de la UPC::Informàtica

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/669212
https://dx.doi.org/10.5821/dissertation-2117-192449

Essential Tools and Strategies for the Participation of Battery Energy Storage Systems in Ancillary Services

Autori: Cardo Miota, Javier

Prispievatelia: University/Department: Universitat Jaume I. Escola de Doctorat

Thesis Advisors: Beltran, Hector, Pérez, Emilio, Belenguer, Enrique

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: European electricity markets, Ancillary services, Battery energy storage systems, Machine learning, Deep learning, Reinforcement learning, Enginyeria, industria i construcció

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/692564

A deep reinforcement learning assisted simulated annealing algorithm for a maintenance planning problem.

Autori: Kosanoglu, Fuat Atmis, Mahir Turan, Hasan Hüseyin

Zdroj: Annals of Operations Research. Aug2024, Vol. 339 Issue 1/2, p79-110. 32p.

Predmety: REINFORCEMENT learning, DEEP reinforcement learning, METAHEURISTIC algorithms, MACHINE learning, SIMULATED annealing

Application of Artificial Intelligence Technologies in Livestock Management.

Alternate Title: Hayvancılıkta Yapay Zekâ Teknolojilerinin Uygulanması.

Autori: DİLAVER, Hatice DİLAVER, Kamil Fatih

Zdroj: Journal of Animal Science & Economics. Jul2025, Vol. 4 Issue 2, p64-74. 11p.

Predmet: Natural language processing, Artificial neural networks, Supervised learning, Artificial intelligence, Agriculture

A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions

Autori: Ozkan-Okay, Merve Akin, Erdal Aslan, Omer a ďalší

Zdroj: IEEE Access. 12:12229-12256

Predmety: Cyberattacks and solutions, deep learning, machine learning, reinforcement learning, AI tools

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-66155
https://doi.org/10.1109/ACCESS.2024.3355547

Bridging Demonstrations and Decisions: Theory and Algorithms for Provable Imitation Learning

Autori: Rajaraman, Nived

Predmety: Computer science, Electrical engineering, Statistics, Computer engineering, Applied mathematics, Behavior Cloning, Imitation Learning, Minimax, Reinforcement Learning, Statistics

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/0dv6h80k
https://escholarship.org/content/qt0dv6h80k/qt0dv6h80k.pdf

FoX: Formation-Aware Exploration in Multi-Agent Reinforcement Learning

Autori: Jo, Yonghyeon Lee, Sunwoo Yeom, Junghyuk a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence. 38:12985-12994

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine Learning (ML) - ML: Reinforcement Learning, Secondary Subject Areas: Multiagent Systems (MAS) - MAS: Multiagent Learning, Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2308.11272

Reinforcement Learning for Dynamic Security Policy Enforcement in Communication Networks.

Autori: Raju, Konda Babu, M. chunchure, Basavaraj a ďalší

Zdroj: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 4, p1304-1311, 8p

Predmety: MACHINE learning, SOFTWARE-defined networking, REINFORCEMENT learning, COMPUTER network security, CYBERTERRORISM

Machine Learning Algorithms: Optimizing Efficiency in AI Applications

Autori: Yadav, Balkrishna Rasiklal¹

Zdroj: International Journal of Engineering and Management Research 14(5):49-57. 2024

Smart manufacturing: MLOps-enabled event-driven architecture for enhanced control in steel production

Autori: Ahmed, BS. Azzalin, T Kassler, A a ďalší

Zdroj: Journal of Systems and Software. 230

Predmety: Advanced machine learning (ML), Deep reinforcement learning (DRL), MLOps-driven architecture, Steel production, Agile manufacturing systems, Architecture, Cost effectiveness, Deep learning, Deep reinforcement learning, Digital twin, E-learning, Industrial research, Intelligent agents, Learning algorithms, Learning systems, Metadata, Network architecture, Reinforcement learning, Smart manufacturing, Software architecture, Sustainable development, Advanced machine learning, Event-driven architectures, Machine learning operation-driven architecture, Machine-learning, Manufacturing machine, Reinforcement learnings, Steelmaking

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-79325

Machine Learning for Warfarin Therapy: A Systematic Review.

Autori: Fülöp, Pavol Tóth, Štefan Porubän, Tibor a ďalší

Zdroj: Pharmaceuticals (14248247); Oct2025, Vol. 18 Issue 10, p1544, 25p

Predmety: MACHINE learning, WARFARIN, RETROSPECTIVE studies, CLINICAL medicine, SAFETY, ANTICOAGULANTS

Reinforcement Learning from Static Datasets: Algorithms, Analysis, and Applications

Autori: Kumar, Aviral

Predmety: Artificial intelligence, control, decision-making, offline RL, Reinforcement learning

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/5786j4qg
https://escholarship.org/content/qt5786j4qg/qt5786j4qg.pdf