Suchergebnisse - Computing methodologies→Machine learning algorithms*

Necessary but not Sufficient: Limitations of Projection Quality Metrics.

Autoren: Machado, A. Behrisch, M. Telea, A.

Quelle: Computer Graphics Forum. Jun2025, Vol. 44 Issue 3, p1-12. 12p.

Schlagwörter: *DESCRIPTIVE statistics, *MULTIVARIATE analysis, *DATA analysis, *QUANTITATIVE research, DIMENSIONAL reduction algorithms, DATA visualization

Learning MAX-SAT Models from Examples using Genetic Algorithms and Knowledge Compilation

Autoren: Berden, Senne Kumar, Mohit Kolb, Samuel et al.

Weitere Verfasser: Berden, Senne Kumar, Mohit Kolb, Samuel et al.

Schlagwörter: constraint learning, Computing methodologies → Machine learning, Machine learning, ddc:004, 46 Information and computing sciences, MAX-SAT

Dateibeschreibung: application/pdf

Zugangs-URL: https://lirias.kuleuven.be/handle/20.500.12942/695199
https://doi.org/10.4230/lipics.cp.2022.8
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.8

LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding

Autoren: Bhowmick, Ayan Meneni, Koushik Danisch, Maximilien et al.

Weitere Verfasser: Bhowmick, Ayan Meneni, Koushik Danisch, Maximilien et al.

Quelle: Proceedings of the 13th International Conference on Web Search and Data Mining. :43-51

Schlagwörter: [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI], 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, [INFO] Computer Science [cs], CCS CONCEPTS • Computing methodologies → Machine learning algorithms, scalability, • Mathematics of computing → Graph algorithms KEYWORDS Network embedding, real-world graph algorithms

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.archives-ouvertes.fr/hal-02999888/file/WSDM2020.pdf
http://dblp.uni-trier.de/db/conf/wsdm/wsdm2020.html#BhowmickMDGM20
https://hal.archives-ouvertes.fr/hal-02999888/document
https://hal.archives-ouvertes.fr/hal-02999888
https://dl.acm.org/doi/pdf/10.1145/3336191.3371800
https://hal.science/hal-02999888v1
https://doi.org/10.1145/3336191.3371800
https://hal.science/hal-02999888v1/document

Learning Metric Fields for Fast Low‐Distortion Mesh Parameterizations.

Autoren: Fargion, G. Weber, O.

Quelle: Computer Graphics Forum. May2025, Vol. 44 Issue 2, p1-14. 14p.

Schlagwörter: *ARTIFICIAL neural networks, HARMONIC maps, TENSOR fields, LAPLACIAN matrices, METRIC spaces, INJECTIVE functions

A Survey of Quantum Machine Learning: Foundations, Algorithms, Frameworks, Data and Applications.

Autoren: Rodríguez-Díaz, Francesc Gutiérrez-Avilés, David Troncoso, Alicia et al.

Quelle: ACM Computing Surveys; Apr2026, Vol. 58 Issue 4, p1-35, 35p

Schlagwörter: ALGORITHMS, QUANTUM computing, MATHEMATICAL functions

The 1st International Workshop on Human-in-the-Loop Applied Machine Learning (HITLAML)

Autoren: YILMA, Bereket Abera Surafel M. Lakew Yogesh Virkar et al.

Quelle: Human-in-the-Loop Applied Machine Learning (HITLAML) (2023-09-04)

Schlagwörter: CCS Concepts: • Computing methodologies → Machine learning algorithms, Machine learning approaches, Learning paradigms, Artificial intelligence, • Human-centered computing → HCI design and evaluation methods, Interactive systems and tools Interactive Machine Learning, Human-centered Artificial Intelligence, Adaptation, Personalization, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques

Relation: https://hitlaml.uni.lu; https://orbilu.uni.lu/handle/10993/59348; info:hdl:10993/59348; https://orbilu.uni.lu/bitstream/10993/59348/1/HITLAML23.pdf

Verfügbarkeit: https://orbilu.uni.lu/handle/10993/59348
https://orbilu.uni.lu/bitstream/10993/59348/1/HITLAML23.pdf

Comprehensive Literature Review on Bio Inspired Optimization-based Path Selection for Message Forwarding in Delay Tolerant Network.

Autoren: Prasad, Ajay Gurung, Sandeep Sharma, Kalpana

Quelle: Grenze International Journal of Engineering & Technology (GIJET); Jan2025, Vol. 11 Issue Part2, p4549-4564, 16p

Schlagwörter: ANT algorithms, PARTICLE swarm optimization, DELAY-tolerant networks, MATHEMATICAL optimization, DISASTER resilience, BIOLOGICALLY inspired computing

Imbalanced Classification with TPG Genetic Programming: Impact of Problem Imbalance and Selection Mechanisms

Autoren: Sourbier, Nicolas Bonnot, Justine Majorczyk, Frédéric et al.

Weitere Verfasser: Sourbier, Nicolas Bonnot, Justine Majorczyk, Frédéric et al.

Quelle: GECCO 2022 - Genetic and Evolutionary Computation Conference ; https://hal.science/hal-03699228 ; GECCO 2022 - Genetic and Evolutionary Computation Conference, Jul 2022, Boston, United States. pp.1-4, ⟨10.1145/3520304.3529008⟩

Schlagwörter: CCS CONCEPTS • Computing methodologies → Machine learning, Artificial intelligence, Genetic programming, Genetic algorithms classification, machine learning, imbalanced data, tangled program graphs, selection, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Geographisches Schlagwort: Boston, United States

Time: Boston, United States

Relation: hal-03699228; https://hal.science/hal-03699228; https://hal.science/hal-03699228/document; https://hal.science/hal-03699228/file/imbalanced_classification_gecco.pdf

Verfügbarkeit: https://hal.science/hal-03699228
https://hal.science/hal-03699228/document
https://hal.science/hal-03699228/file/imbalanced_classification_gecco.pdf
https://doi.org/10.1145/3520304.3529008

Optimized Diabetes Prediction Using Soft Computing: CURE-ADASYN for Imbalance and Advanced Deep Learning Classification Methods.

Autoren: Abinaya, V. Chitra, K.

Quelle: International Journal of Environmental Sciences (2229-7359); 2025 Special Issue, Vol. 11, p170-178, 9p

Schlagwörter: DIABETES, DEEP learning, GREY Wolf Optimizer algorithm, PARTICLE swarm optimization, LONG short-term memory, FORECASTING, SOFT computing

Flow-Time Minimization for Timely Data Stream Processing in UAV-Aided Mobile Edge Computing.

Autoren: Xu, Zichuan Qiao, Haiyang Liang, Weifa et al.

Quelle: ACM Transactions on Sensor Networks; May2024, Vol. 20 Issue 3, p1-28, 28p

Schlagwörter: MOBILE computing, EDGE computing, ONLINE algorithms, ELECTRONIC data processing, 5G networks, POWER resources

Aging and rejuvenating strategies for fading windows in multi-label classification on data streams

Autoren: Roseberry, Martha Dzeroski, Saso Bifet, Albert et al.

Weitere Verfasser: Roseberry, Martha Dzeroski, Saso Bifet, Albert et al.

Quelle: SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing ; Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, SAC 2023, Tallinn, Estonia, March 27-31, 2023 ; https://hal.science/hal-04468384 ; Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, SAC 2023, Tallinn, Estonia, March 27-31, 2023, Mar 2023, Talinn, Estonia. pp.390--397, ⟨10.1145/3555776.3577625⟩

Schlagwörter: Computing methodologies → Machine learning algorithms, Machine Learning, Data Streams, Multi-label Learning, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geographisches Schlagwort: Talinn, Estonia

Time: Talinn, Estonia

Verfügbarkeit: https://hal.science/hal-04468384
https://doi.org/10.1145/3555776.3577625

Learning with Differentiable Algorithms

Autoren: Petersen, Felix

Schlagwörter: machine learning, optimization, differentiable, continuous relaxation, computer science, algorithms, neural networks, Computing methodologies~Machine learning, ddc:004

Dateibeschreibung: application/pdf

Relation: 181565192X

Verfügbarkeit: http://nbn-resolving.de/urn:nbn:de:bsz:352-2-1qlgm6rvkz9m08

Prediction of compressive strength of BFRC using soft computing techniques.

Autoren: Almohammed, Fadi Thakur, Mohindra S.

Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Jan2024, Vol. 28 Issue 2, p1391-1408, 18p

Schlagwörter: SOFT computing, FIBER-reinforced concrete, FLY ash, RANDOM forest algorithms

Synaptic AI: Bridging Neural Dynamics and Deep Learning for Next-Generation Computation.

Autoren: Kumbhar, Gaurang Shelke, Srushti Totawad, Priti

Quelle: International Scientific Journal of Engineering & Management; Apr2025, Vol. 4 Issue 4, p1-9, 9p

Schlagwörter: ARTIFICIAL neural networks, ARTIFICIAL intelligence, MACHINE learning, DEEP learning, SMART devices

Quantum AI for psychiatric diagnosis: enhancing dementia classification with quantum machine learning.

Autoren: Amin, Javaria Ali, Muhammad Umair Islam, Muhammad Zubair et al.

Quelle: Frontiers in Psychiatry; 2025, p1-11, 11p

A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization.

Autoren: YANDI LI HAOBO GAO YUNXUAN GAO et al.

Quelle: ACM Transactions on Knowledge Discovery from Data; Nov2023, Vol. 17 Issue 9, p1-50, 50p

Schlagwörter: COMBINATORIAL optimization, REINFORCEMENT learning, DEEP reinforcement learning, APPROXIMATION algorithms, SOCIAL computing, ARTIFICIAL intelligence, ONLINE social networks

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators.

Autoren: ABADAL, SERGI JAIN, AKSHAY GUIRADO, ROBERT et al.

Quelle: ACM Computing Surveys; Dec2022, Vol. 54 Issue 9, p1-38, 38p

Schlagwörter: ALGORITHMS, TELECOMMUNICATION systems

Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete.

Autoren: Awoyera, Paul O. Adetola, Joshua Nayeemuddin, Mohammed et al.

Quelle: Advances in Civil Engineering; 10/10/2025, Vol. 2025, p1-13, 13p

Schlagwörter: FLY ash, MACHINE learning, CONCRETE, ECOLOGICAL impact, SOFT computing, ENVIRONMENTAL impact analysis, CONSTRUCTION industry, SUSTAINABILITY

Modeling economic growth in pandemic times with machine learning regression algorithms.

Alternate Title: Modelado del crecimiento económico durante la pandemia con algoritmos de regresión de aprendizaje automático. (Spanish)

Autoren: Alejandro Navarro-Acosta, J. Soto-Mendoza, Valeria Policardo, Laura et al.

Quelle: Mexican Journal of Economics & Finance / Revista Mexicana de Economia y Finanzas; ene-mar2025, Vol. 20 Issue 1, p1-33, 33p

Schlagwörter: COVID-19 pandemic, MACHINE learning, REGRESSION trees, RANDOM forest algorithms, ESTIMATION theory

Mathematics-Inspired Models: A Green and Interpretable Learning Paradigm for Multimedia Computing.

Autoren: Gao, Lei Liu, Kai Guo, Zheng et al.

Quelle: ACM Transactions on Multimedia Computing, Communications & Applications; Jul2025, Vol. 21 Issue 7, p1-22, 22p

Schlagwörter: ARTIFICIAL neural networks, MACHINE learning, MULTIMEDIA systems, ARTIFICIAL intelligence, SUSPICION