Výsledky vyhledávání - Computing methodologies Machine learning

Current Stage and Future Perspectives for Homology Modeling, Molecular Dynamics Simulations, Machine Learning with Molecular Dynamics, and Quantum Computing for Intrinsically Disordered Proteins and Proteins with Intrinsically Disordered Regions

Autoři: Orkid Coskuner-Weber Vladimir N. Uversky TAÜ, Fen Fakültesi, Moleküler Biyoteknoloji Bölümü

Přispěvatelé: Orkid Coskuner-Weber Vladimir N. Uversky TAÜ, Fen Fakültesi, Moleküler Biyoteknoloji Bölümü

Zdroj: Current Protein & Peptide Science. 25:163-171

Témata: 0301 basic medicine, 0303 health sciences, Machine learning with molecular dynamics, Intrinsically disordered proteins, Molecular dynamics simulations, Protein Conformation, Homology modeling, Quantum computing, Molecular Dynamics Simulation, Computing Methodologies, Intrinsically Disordered Proteins, Machine Learning, 03 medical and health sciences, Proteins with intrinsically disordered regions, Quantum Theory

Popis souboru: image/jpeg

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38275091
https://hdl.handle.net/20.500.12846/1228

Breast Cancer Detection Using Machine Learning with Thermograms in an Edge Computing Scenario

Autoři: Tahmooresi, Maryam Remondo Bueno, David Alcober Segura, Jesús Ángel

Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Témata: Enginyeria de la telecomunicació::Aspectes socials [Àrees temàtiques de la UPC], 02 engineering and technology, Computing methodologies, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament del senyal en les telecomunicacions, 3. Good health, Telecomunicació de banda ampla, Sistemes de, Machine learning approaches, Computational neuroscience, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Broadband communication systems, Neurociència computacional, Neural networks, Enginyeria de la telecomunicació::Processament del senyal::Processament del senyal en les telecomunicacions [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Aspectes socials

Popis souboru: application/pdf

Přístupová URL adresa: https://upcommons.upc.edu/handle/2117/353841
https://hdl.handle.net/2117/353841
https://doi.org/10.1145/3469258.3469850

Tabular and Deep Learning for the Whittle Index

Autoři: Robledo Relaño, Francisco Borkar, Vivek Ayesta, Urtzi a další

Přispěvatelé: Robledo Relaño, Francisco Borkar, Vivek Ayesta, Urtzi a další

Zdroj: ACM Transactions on Modeling and Performance Evaluation of Computing Systems. 9:1-21

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, CCS Concepts: Computing methodologies → Sequential decision making Machine learning Reinforcement Learning Whittle Index Markov Decision Problem Multi-armed Restless Bandit, Computer Science - Machine Learning, 0209 industrial biotechnology, Computer Science - Artificial Intelligence, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], 02 engineering and technology, Reinforcement Learning, 01 natural sciences, Markov Decision Problem, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Machine Learning (cs.LG), CCS Concepts, Artificial Intelligence (cs.AI), [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Whittle Index, Computing methodologies → Sequential decision making Machine learning, 0101 mathematics

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2406.02057
https://hal.science/hal-04599291v1/document
https://doi.org/10.1145/3670686
https://hal.science/hal-04599291v1

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework

Autoři: Tayyabah Hasan Fahad Ahmad Muhammad Rizwan a další

Zdroj: Comput Intell Neurosci

Témata: Deep Learning, 0202 electrical engineering, electronic engineering, information engineering, Quantum Theory, 02 engineering and technology, Computing Methodologies, Algorithms, Research Article

Přístupová URL adresa: https://downloads.hindawi.com/journals/cin/2022/6138434.pdf
https://pubmed.ncbi.nlm.nih.gov/35035461

Quantum computing and machine learning for Arabic language sentiment classification in social media

Autoři: Omar Ahmed Tarek Abd El‐Hafeez

Zdroj: Sci Rep
Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)

Témata: Quantum Computation, Artificial intelligence, Economics, Science, Materials Science, Computing Methodologies, Quantum mechanics, Article, Quantum, Machine Learning, Sentiment analysis, Task (project management), Machine Translation, Artificial Intelligence, Quantum Computing and Simulation, Quantum computer, Field (mathematics), Machine learning, Sentiment Analysis, Materials Chemistry, FOS: Mathematics, Humans, Language, Natural Language Processing, Quantum Machine Learning, Precision and recall, Arabic, Accelerating Materials Innovation through Informatics, Natural language processing, Physics, Pure mathematics, Linguistics, Computer science, FOS: Philosophy, ethics and religion, Management, Philosophy, Physical Sciences, Computer Science, FOS: Languages and literature, Medicine, Quantum Theory, Recall, Quantum Information, Social Media, Quantum machine learning, Mathematics

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37828056
https://doaj.org/article/69cf58a6790249f791954b84c33753ed

Comparing Teaching Strategies of a Machine Learning-based Prosthetic Arm

Autoři: Sungeelee, Vaynee Sanchez, Téo Jarrasse, Nathanael a další

Přispěvatelé: Sungeelee, Vaynee Sanchez, Téo Jarrasse, Nathanael a další

Zdroj: Proceedings of the 29th International Conference on Intelligent User Interfaces. :715-730

Témata: Machine Learning, Human-centered computing → Empirical studies in HCI, Training curriculum, Mental model, Interactive Machine Teaching, Computing methodologies → Learning from demonstrations, Accessibility technologies, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], Myoelectric prosthesis

Popis souboru: application/pdf

Přístupová URL adresa: https://hal.science/hal-04527854v1

ImPORTance - Machine Learning-Driven Analysis of Global Port Significance and Network Dynamics for Improved Operational Efficiency

Autoři: Carlini, Emanuele Di Gangi, Domenico Monteiro de Lira, Vinicius a další

Zdroj: SSTD '25: Proceedings of the 19th International Symposium on Spatial and Temporal Data.

Témata: Information systems, Location based services, Computing methodologies, Applied computing, Transportation, Data- och informationsvetenskap, Computer and Information Sciences Computer Science

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-140412
https://doi.org/10.1145/3748777.3748792

AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods

Autoři: Muhammad Usman Tariq Shuhaida Binti Ismail

Zdroj: Osong Public Health Res Perspect
Osong Public Health and Research Perspectives, Vol 15, Iss 2, Pp 115-136 (2024)

Témata: 0301 basic medicine, deep learning, RC952-1245, Infectious and parasitic diseases, RC109-216, 02 engineering and technology, algorithms, artificial intelligence, neural networks, 3. Good health, 03 medical and health sciences, Special situations and conditions, 0202 electrical engineering, electronic engineering, information engineering, computing methodologies, Original Article, QA Mathematics, computer

Popis souboru: text

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38621765
https://doaj.org/article/14eef2dfd4f24c2e88d4158cd9ec76fc

Evaluation model of physical education teaching effect based on machine learning algorithm with biomechanical integration.

Autoři: Liu, Xiaoli

Zdroj: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 3, p1-18, 18p

Témata: MACHINE learning, BIOMECHANICS, EFFECTIVE teaching, PHYSICAL education, EVALUATION methodology, TEACHING methods, BIOLOGICALLY inspired computing, SCHOOL children

Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning

Autoři: Gianluca Mittone Nicoló Tonci Robert Birke a další

Zdroj: Proceedings of the 20th ACM International Conference on Computing Frontiers. :73-83

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing, Computing methodologies, Distributed computing methodologies, Distributed algorithms, Machine learning, Machine learning approaches, Neural networks, Hardware, Emerging technologies, Analysis and design of emerging devices and systems, Emerging architectures, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Edge Computing, Energy Consumption, Federated Learning, Green Computing, RISC-V, 02 engineering and technology, Distributed, Parallel, and Cluster Computing (cs.DC), 01 natural sciences, RISC-V, Energy Consumption, Federated Learning, Edge Computing, Green Computing, Machine Learning (cs.LG)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2302.07946
https://hdl.handle.net/11568/1202687
https://doi.org/10.1145/3587135.3592211
https://hdl.handle.net/2318/1898473
https://doi.org/10.1145/3587135.3592211
https://arxiv.org/abs/2302.07946

KEGNN: Knowledge-Enhanced Graph Neural Networks for User Engagement Prediction

Autoři: Fan, Ching-Hao Zhou, Hao Sun, Yao a další

Přispěvatelé: Fan, Ching-Hao Zhou, Hao Sun, Yao a další

Zdroj: Proceedings of the 2025 International Conference on Multimedia Retrieval. :275-283

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], user engagement prediction, Information extraction, Social networks knowledge sharing, graph learning, [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI], [SHS.STAT] Humanities and Social Sciences/Methods and statistics, graph neural networks, natural language processing, Neural networks, Computing methodologies, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML]

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Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR

Autoři: Alexander Tropsha Olexandr Isayev Alexandre Varnek a další

Zdroj: Nature Reviews Drug Discovery. 23:141-155

Témata: Deep Learning, Artificial Intelligence, Drug Design, Drug Discovery, Humans, Quantitative Structure-Activity Relationship, Quantum Theory, Computing Methodologies, 3. Good health

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38066301

ImmersiveIML – Immersive interactive machine learning for 3D point cloud classification: the neural network at your fingertips

Autoři: Cordeil, Maxime Billy, Thomas Mellado, Nicolas a další

Přispěvatelé: Cordeil, Maxime Billy, Thomas Mellado, Nicolas a další

Zdroj: 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). :81-85

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Gestural input, Visu- alization techniques, Human-centered computing, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], Interaction techniques, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], Interaction paradigms, Virtual reality, Computing methodologies, Neural networks, Visualization

Popis souboru: application/pdf

Přístupová URL adresa: https://hal.science/hal-04246601v1
https://hal.science/hal-04246601v1/document
https://doi.org/10.1109/ismar-adjunct60411.2023.00025

Application of soft computing methodologies to predict the 28-day compressive strength of shotcrete: a comparative study of individual and hybrid models

Autoři: Mahtab Torkan Hamid Kalhori Mohammad Hossein Jalalian

Zdroj: Rudarsko-geološko-naftni Zbornik, Vol 36, Iss 5, Pp 33-48 (2021)

Témata: QE1-996.5, Mining engineering. Metallurgy, Compressive Strength, TN1-997, 0211 other engineering and technologies, Geology, 02 engineering and technology, Machine learning techniques, Shotcrete, Hybrid model, 0201 civil engineering

Přístupová URL adresa: https://hrcak.srce.hr/file/386657
https://doaj.org/article/f5be8c1eb965412db7e306d40fa05da6

Machine Learning: A First Introduction for Political Research

Autoři: Moses, Laura M. Box-Steffensmeier, Janet M. Box-Steffensmeier, Janet M., book editor a další

Přispěvatelé: Moses, Laura M. Box-Steffensmeier, Janet M. Box-Steffensmeier, Janet M., book editor a další

Zdroj: Oxford Handbook of Engaged Methodological Pluralism in Political Science.

Dostupnost: https://doi.org/10.1093/oxfordhb/9780192868282.013.49

Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing: A Survey

Autoři: Le Duc T. Leiva R. G. Casari P. a další

Zdroj: IMDEA Networks Institute Digital Repository
instname
IMDEA Networks Institute
ACM Computing Surveys

Témata: distributed systems, Autoscaling, Cloud computing, Consolidation, Distributed systems, Edge computing, Machine learning, Optimization, Placement, Reliability, Remediation, cloud computing, distributed architectures, architectures, 02 engineering and technology, placement, machine learning, edge computing, modeling and simulation, autoscaling, remediation, 0202 electrical engineering, electronic engineering, information engineering, computing methodologies, consolidation, optimization, dependable and fault-tolerant systems and networks, general and reference

Popis souboru: application/pdf

Přístupová URL adresa: https://iris.unitn.it/retrieve/handle/11572/253114/306685/mlsurvey.pdf
http://hdl.handle.net/20.500.12761/738
http://eprints.networks.imdea.org/2034/1/mlsurvey.pdf
https://dspace.networks.imdea.org/handle/20.500.12761/738
http://www.diva-portal.org/smash/record.jsf?pid=diva2:1351519
https://doi.org/10.1145/3341145
https://zenodo.org/record/3471441
http://umu.diva-portal.org/smash/record.jsf?pid=diva2:1351519&language=en
https://hdl.handle.net/11572/253114
http://dl.acm.org/citation.cfm?id=J204
https://doi.org/10.1145/3341145

A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference

Autoři: Pol Puigdemont Enrico Russo Axel Wassington a další

Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Proceedings of the ASP-DAC 2025

Témata: FOS: Computer and information sciences, Application-specific VLSI designs, Computer Science - Machine Learning, Electronic design automation, accelerator, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Modeling and simulation, graph neural network (GNN), scheduler, Computing methodologies, Machine Learning (cs.LG), Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors, Machine learning approaches, Application specific processors, Hardware, Machine learning, Hardware Architecture (cs.AR), High-level and register-transfer level synthesis, Hardware-software codesign, regression, Very large scale integration design, Computer Science - Hardware Architecture, Neural networks

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2411.16342
https://hdl.handle.net/2117/442380
https://doi.org/10.1145/3658617.3697660
https://hdl.handle.net/20.500.11769/670589
https://doi.org/10.1145/3658617.3697660

Data Science and Reliable Machine Learning: Proceedings from the 4th Codassca Workshop Yerevan, Armenia, October 2024

Přispěvatelé: Hajian, Aram Baloian, Nelson Inoue, Tomoo a další

Témata: Computer system organization -- Computing methodologies -- Applied computing -- Human-centered computing -- Security -- CODASSCA, ddc:004, schema.org/Book [http], Fakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Computergraphik und Wissenschaftliches Rechnen

Přístupová URL adresa: https://duepublico2.uni-due.de/servlets/MCRFileNodeServlet/duepublico_derivate_00081943/Proceedings_4th_Codassca_Workshop_2024.pdf

Explaining the Explainers in Graph Neural Networks: a Comparative Study

Autoři: Antonio Longa Steve Azzolin Gabriele Santin a další

Přispěvatelé: Antonio Longa Steve Azzolin Gabriele Santin a další

Zdroj: ACM Computing Surveys

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computing methodologies, Neural networks, Explainability, graph neural networks, Machine Learning (cs.LG)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2210.15304
https://dl.acm.org/doi/10.1145/3696444
https://doi.org/10.1145/3696444
https://hdl.handle.net/11572/437366

Walleye (Sander vitreus, Mitchill 1818) age and sex classification using innovative supervised and unsupervised machine learning and soft computing methodologies

Autoři: Despina Selina Spanou Panagiota Petroudi Elli Dimou a další

Zdroj: Fisheries Research. 275:107031