Výsledky vyhledávání - Theory of computation → Unsupervised learning and clustering

An Expedited Route to Optical and Electronic Properties at Finite Temperature via Unsupervised Learning

Autoři: Fulvio Perrella Federico Coppola Nadia Rega a další

Zdroj: Molecules, Vol 28, Iss 8, p 3411 (2023)

Témata: density functional theory, machine learning, computations of optical spectra, molecular dynamics, clustering techniques, Organic chemistry, QD241-441

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1420-3049/28/8/3411; https://doaj.org/toc/1420-3049

Přístupová URL adresa: https://doaj.org/article/9260b350071444e6ace08f9ab9b75bc7

Noisy k-Means++ Revisited

Autoři: Grunau, Christoph Özüdoğru, Ahmet Alper Rozhoň, Václav a další

Přispěvatelé: Grunau, Christoph Özüdoğru, Ahmet Alper Rozhoň, Václav a další

Zdroj: Leibniz International Proceedings in Informatics (LIPIcs), 274
31st Annual European Symposium on Algorithms (ESA 2023)

Témata: Theory of computation → Approximation algorithms analysis, Theory of computation → Unsupervised learning and clustering, Clustering, K-means, K-means++, Adversarial noise

Popis souboru: application/application/pdf

Přístupová URL adresa: http://hdl.handle.net/20.500.11850/637195

A distributed unsupervised learning algorithm and its suitability to physical based observation.

Autoři: Hes, Radek Gioroli, Giacomo

Zdroj: International Journal of Parallel, Emergent & Distributed Systems. Aug2022, Vol. 37 Issue 4, p443-455. 13p.

Témata: *MACHINE learning, *K-means clustering, *RANDOM noise theory, *PRIOR learning, *POINT set theory

Geografický termín: NEW Zealand

EduClust - A Visualization Application for Teaching Clustering Algorithms

Autoři: Fuchs, Johannes Isenberg, Petra Bezerianos, Anastasia a další

Přispěvatelé: Fuchs, Johannes Isenberg, Petra Bezerianos, Anastasia a další

Témata: Information Visualization, 4. Education, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, Applied computing, Interactive learning environments, 02 engineering and technology, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], 0503 education, Unsupervised learning and clustering, Theory of computation

Popis souboru: application/pdf

Přístupová URL adresa: https://inria.hal.science/hal-02103293v1
https://hal.univ-lorraine.fr/LRI-HCC/hal-02103293v1
https://doi.org/10.2312/eged.20191023
https://kops.uni-konstanz.de/handle/123456789/46436
https://hal.inria.fr/hal-02103293/document
https://dblp.uni-trier.de/db/conf/eurographics/eg-education2019.html#FuchsIBMK19
https://diglib.eg.org/handle/10.2312/eged20191023
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-1ovs37tv6vmi82

Application of Artificial Intelligence Technologies in Livestock Management.

Alternate Title: Hayvancılıkta Yapay Zekâ Teknolojilerinin Uygulanması.

Autoři: DİLAVER, Hatice DİLAVER, Kamil Fatih

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

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

Profiling DRDoS Attacks with Data Analytics Pipeline

Autoři: Berti-Équille, Laure Zhauniarovich, Yury UMR 228 Espace-Dev, Espace pour le développement a další

Přispěvatelé: Berti-Équille, Laure Zhauniarovich, Yury UMR 228 Espace-Dev, Espace pour le développement a další

Zdroj: the 2017 ACM ; https://hal.science/hal-01829013 ; the 2017 ACM, Nov 2017, Singapore, Singapore. ⟨10.1145/3132847.3133155⟩

Témata: Information systems, Theory of computation, Data analytics, Networks, Unsupervised learning and cluster- ing, Clustering, Computing methodologies, Denial-of-service attacks, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Singapore

Dostupnost: https://hal.science/hal-01829013
https://hal.science/hal-01829013v1/document
https://hal.science/hal-01829013v1/file/CIKM2017.pdf
https://doi.org/10.1145/3132847.3133155

Spot the Bot: Distinguishing Human-Written and Bot-Generated Texts Using Clustering and Information Theory Techniques

Autoři: Gromov, Vasilii Dang, Quynh Nhu

Témata: Computer Science - Computation and Language, text

URL: http://arxiv.org/abs/2311.11441

iCVI-ARTMAP: Accelerating and improving clustering using adaptive resonance theory predictive mapping and incremental cluster validity indices

Autoři: da Silva, Leonardo Enzo Brito Rayapati, Nagasharath Wunsch II, Donald C.

Témata: Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2008.09903

Kalathos+: Construcción de datasets para la clasificación automática de fragmentos de vasijas cerámicas de torno

Autoři: Segura, Rafael J. Rueda, Antonio J. Ogáyar, Carlos J. a další

Témata: Applied computing, Arts and humanities, Unsupervised learning and clustering, Computational geometry, CCS Concepts: Applied computing --> Arts and humanities, Theory of computation --> Unsupervised learning and clustering, Theory of computation

Computation of failure probability via hierarchical clustering.

Autoři: Yin, Chao Kareem, Ahsan

Zdroj: Structural Safety. Jul2016, Vol. 61, p67-77. 11p.

Témata: *HIERARCHICAL clustering (Cluster analysis), *FAILURE analysis, *PROBABILITY theory, *MARKOV chain Monte Carlo, *SUPPORT vector machines, *ARTIFICIAL neural networks, *SUPERVISED learning

The Poincaré-Shannon Machine: Statistical Physics and Machine Learning Aspects of Information Cohomology

Autoři: Pierre Baudot

Zdroj: Entropy, Vol 21, Iss 9, p 881 (2019)

Témata: algebraic topology, machine learning, information theory, statistical physics, deep neural networks, unsupervised learning, multivariate mutual information, statistical dependences, k-body interactions, synergy, clustering, Science, Astrophysics, QB460-466, Physics, QC1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1099-4300/21/9/881; https://doaj.org/toc/1099-4300

Přístupová URL adresa: https://doaj.org/article/087acc060be245c5ade0b77bbe689649

Unsupervised feature learning based on sparse coding and spectral clustering for segmentation of synthetic aperture radar images.

Autoři: Rahmani, Masoumeh Akbarizadeh, Gholamreza

Zdroj: IET Computer Vision (Wiley-Blackwell); 2015, Vol. 9 Issue 5, p629-638, 10p

Témata: COMPUTER vision, FEATURE extraction, SUPERVISED learning, CODING theory, IMAGE segmentation, SYNTHETIC aperture radar

Evaluation of Density Functional Theory-Generated Data for Infrared Spectroscopy of Novel Psychoactive Substances Using Unsupervised Learning.

Autoři: dos Santos, Christiano Bruni, Aline Thais

Zdroj: Psychoactives; Jun2024, Vol. 3 Issue 2, p265-284, 20p

Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.

Autoři: Jobarteh, Bubacarr Mincu-Iorga, Madalina Gavojdian, Dinu a další

Zdroj: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Longitudinal Data Clustering Methods: A Systematic Review.

Autoři: Tafti, Arefeh Dehghani Jahani, Yunes Jambarsang, Sara a další

Zdroj: Journal of Biostatistics & Epidemiology; 2023, Vol. 9 Issue 4, p396-411, 16p

Témata: K-means clustering, RESEARCH, EUCLIDEAN distance, LEARNING, ALGORITHMS, LONGITUDINAL method, RESEARCH personnel, DATA analysis

Reviews & Products: GOOGLE Scholar (Web resource), PUBMED (Online service)

An Ensemble and Multi-View Clustering Method Based on Kolmogorov Complexity

Autoři: Juan Zamora Jérémie Sublime

Zdroj: Entropy, Vol 25, Iss 2, p 371 (2023)

Témata: clustering, Kolmogorov complexity, multi-view learning, information theory, Science, Astrophysics, QB460-466, Physics, QC1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1099-4300/25/2/371; https://doaj.org/toc/1099-4300

Přístupová URL adresa: https://doaj.org/article/9bcb4a42714f4db781657fe56bd19878

Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands.

Autoři: Long, Yang Xue, Haoran Zhang, Baile

Zdroj: Nature Machine Intelligence; Aug2024, Vol. 6 Issue 8, p904-910, 7p

The Use of Machine Learning to Predict Prevalence of Subclinical Mastitis in Dairy Sheep Farms.

Autoři: Kiouvrekis, Yiannis Vasileiou, Natalia G. C. Katsarou, Eleni I. a další

Zdroj: Animals (2076-2615); Aug2024, Vol. 14 Issue 16, p2295, 21p

Témata: SHEEP ranches, MACHINE learning, SUPERVISED learning, SUPPORT vector machines, DAIRY farming, SHEEP farming

Improved cattle farm classification: leveraging machine learning and linked national datasets.

Autoři: Schnidrig, Guy-Alain Struchen, Rahel Schärrer, Sara a další

Zdroj: Frontiers in Veterinary Science. 2025, p1-14. 14p.

A Combination of FPU-Net and Feature Clustering Methods for Accurate Segmentation of Femoral Neck in Radiographic Diagnosis.

Autoři: Chen, Y. Y. Chuang, C. H. Hsieh, S. L. a další

Zdroj: Diagnostics (2075-4418); Sep2023, Vol. 13 Issue 17, p2855, 14p

Témata: FEMUR neck, RADIOSCOPIC diagnosis, COMPUTER-aided diagnosis, SUPERVISED learning, DEEP learning, HIP fractures