Suchergebnisse - "Machine learning Research."
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1
Autoren: et al.
Quelle: Br J Sports Med
Schlagwörter: SDG-03: Good health and well-being, Machine learning research, SDG-09: Industry, Injury risk prediction, Risk Assessment, Machine Learning, 03 medical and health sciences, Logistic Models, 0302 clinical medicine, Sports-related injuries, Area Under Curve, Athletic Injuries, Humans, Systematic Review, Sports, innovation and infrastructure
Dateibeschreibung: application/pdf
Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39613453
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Autoren: et al.
Quelle: Journal of computational social science
Schlagwörter: Artificial intelligence, Active learning, 4609 Information systems, Semi-Supervised Learning, Annotation, Social Sciences, Active Learning, 02 engineering and technology, International trade, Fabric Defect Detection in Industrial Applications, Quantum mechanics, 7. Clean energy, Annotation effort, Industrial and Manufacturing Engineering, Learning with Noisy Labels in Machine Learning, 12. Responsible consumption, Engineering, Deep Learning, Sociology, Artificial Intelligence, Meta-Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Entropy (arrow of time), Business, Retail image analysis, Active Learning in Machine Learning Research, 4701 Communication and media studies, Physics, 4. Education, Retraining, 4410 Sociology, Social Sciences, Mathematical Methods, Active learning (machine learning), 15. Life on land, Computer science, Algorithm, Computer Science, Physical Sciences, Instance segmentation, Mathematics, Mathematical Methods In Social Sciences, Robust Learning
Zugangs-URL: https://
research .tilburguniversity.edu/en/publications/544d20d5-2b8e-4483-b9dd-b2be4d161c17
https://doi.org/10.1007/s42001-024-00266-7
https://lirias.kuleuven.be/handle/20.500.12942/744482
https://doi.org/10.1007/s42001-024-00266-7
https://repository.uantwerpen.be/docstore/d:irua:23253
https://hdl.handle.net/10067/2054360151162165141 -
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Autoren: et al.
Quelle: International Journal of Social Science and Human Research.
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Autoren:
Quelle: ESAIM: Probability and Statistics. 28:132-160
Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Metric (unit), Learning and Inference in Bayesian Networks, Economics, Separable space, Space (punctuation), Mathematical analysis, Metric Spaces, Machine Learning (cs.LG), Computational Complexity and Algorithmic Information Theory, Artificial Intelligence, Euclidean space, FOS: Mathematics, Active Learning in Machine Learning Research, Pure mathematics, Discrete mathematics, Minkowski–Bouligand dimension, Computer science, Packing dimension, Operating system, Dimension (graph theory), Operations management, Computational Theory and Mathematics, Computer Science, Physical Sciences, Metric space, Fractal dimension, Fractal, 62H30, 54F45, Mathematics, Consistency (knowledge bases)
Zugangs-URL: http://arxiv.org/abs/2305.17282
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Autoren: Zaid Ibrahim
Quelle: European Journal of Theoretical and Applied Sciences. 1:105-114
Schlagwörter: Algebraic number, Automaton, Economics, Automata Theory and Formal Languages, Macroeconomics, 0211 other engineering and technologies, 02 engineering and technology, Mathematical analysis, 12. Responsible consumption, Theoretical computer science, Artificial Intelligence, 11. Sustainability, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Production (economics), Active Learning in Machine Learning Research, Scheme (mathematics), Algebra over a field, Arithmetic, Text Compression and Indexing Algorithms, 4. Education, Formal Languages, Pure mathematics, Semantics (computer science), Discrete mathematics, 15. Life on land, Substitution (logic), Computer science, Process (computing), Programming language, Computational Theory and Mathematics, 13. Climate action, Computer Science, Physical Sciences, 8. Economic growth, Binary number, Mathematics
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Autoren: et al.
Quelle: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). :5767-5791
Schlagwörter: Artificial neural network, FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial intelligence, Economics, Semi-Supervised Learning, Generalization, Overfitting, 02 engineering and technology, Mathematical analysis, 01 natural sciences, Machine Learning (cs.LG), Task (project management), Engineering, Artificial Intelligence, Boolean function, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Active Learning in Machine Learning Research, Natural Language Processing, 0105 earth and related environmental sciences, Transformer, Computer Science - Computation and Language, Inductive bias, Text Compression and Indexing Algorithms, Voltage, Computer science, Management, Algorithm, Multi-task learning, Electrical engineering, Computer Science, Physical Sciences, Computation and Language (cs.CL), Mathematics
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Autoren:
Quelle: IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:9669-9680
Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial intelligence, Semi-Supervised Learning, Handling Imbalanced Data in Classification Problems, Active Learning, 02 engineering and technology, Model selection, Learning with Noisy Labels in Machine Learning, Machine Learning (cs.LG), Context (archaeology), Selection (genetic algorithm), Artificial Intelligence, Meta-Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Active Learning in Machine Learning Research, Data mining, Biology, Cost-Sensitive Learning, Paleontology, Cross-validation, Computer science, Process (computing), Operating system, Computer Science, Physical Sciences, Algorithms, Learning Curve, Robust Learning, Labeled data, Training set
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Autoren:
Quelle: Journal of Computational and Graphical Statistics. 32:1348-1360
Schlagwörter: FOS: Computer and information sciences, Artificial neural network, Artificial intelligence, Economics, Computational Mechanics, Sample size determination, Statistics - Computation, Estimator, Mathematical analysis, Engineering, Artificial Intelligence, FOS: Mathematics, Optimization Methods in Machine Learning, Large-Scale Optimization, Active Learning in Machine Learning Research, Computation (stat.CO), Economic growth, Stochastic Gradient Descent, Computer network, Gradient descent, Mathematical optimization, Statistics, Fixed point, Rate of convergence, Theory and Applications of Compressed Sensing, Applied mathematics, Computer science, Algorithm, Channel (broadcasting), Computer Science, Physical Sciences, Computation, Convergence (economics), Mathematics
Zugangs-URL: http://arxiv.org/abs/2304.06564
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9
Autoren:
Schlagwörter: Artificial intelligence, Machine learning, Human-Machine Interaction, Ethics in Artificial Intelligence, Computational Linguistics, Cognitive Science, Cognitive Science/education, Cognitive Science/methods, Cognitive Science/ethics, Human-in-the-Loop System, Machine Learning Research, AI Ethics
Relation: https://zenodo.org/records/17231346; oai:zenodo.org:17231346; https://doi.org/10.5281/zenodo.17231346
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Autoren: et al.
Quelle: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 4. :19-42
Schlagwörter: FOS: Computer and information sciences, Parallel computing, Computer Science - Machine Learning, Artificial intelligence, Hyperparameter Optimization, Compiler, 02 engineering and technology, Bayesian probability, Learning with Noisy Labels in Machine Learning, Machine Learning (cs.LG), Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Parallel Computing and Performance Optimization, GPU Computing, Computer architecture, Active Learning in Machine Learning Research, Bayesian optimization, Computer Science - Programming Languages, Computer Science - Performance, Performance Optimization, Computer science, Programming language, Performance (cs.PF), Hardware and Architecture, Optimizing compiler, Computer Science, Physical Sciences, Programming Languages (cs.PL)
Zugangs-URL: http://arxiv.org/abs/2212.11142
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Autoren:
Quelle: Machine Learning. 113:4903-4923
Schlagwörter: Artificial intelligence, Class (philosophy), Conditional probability distribution, Semi-Supervised Learning, Handling Imbalanced Data in Classification Problems, 02 engineering and technology, Pattern recognition (psychology), Mathematical analysis, Bandwidth (computing), Engineering, Artificial Intelligence, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Ensemble Methods, Active Learning in Machine Learning Research, SMOTE, Computer network, Imbalanced Data, Distribution (mathematics), Electricity Theft Detection in Smart Grids, Motion (physics), 4. Education, Oversampling, Statistics, Computer science, Algorithm, Computer Science, Physical Sciences, Interpolation (computer graphics), Mathematics
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Autoren: et al.
Quelle: Procedia CIRP. :906-911
Schlagwörter: assembly, image processing, machine learning, robot, Costs, Object recognition, Processing, Robot programming, Robotics, Advanced technology, Assembly process, Assembly systems, Image processing - methods, Images processing, Machine learning research, Object trajectories, Objects recognition, Processing approach, Robotic assembly
Dateibeschreibung: print
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Autoren:
Quelle: ESANN 2021 Proceedings - 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. :441-446
Schlagwörter: Backpropagation, Neural networks, Torsional stress, Bayesian, Cortexes, Internal representation, Learn+, Machine learning research, Neural network model, Neural-networks, Plausible model, Semi-supervised, Unlabeled data, Bayesian networks
Dateibeschreibung: print
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Quelle: Zhongguo quanke yixue, Vol 27, Iss 10, Pp 1271-1276 (2024)
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Autoren:
Quelle: Machine Learning. 112:1131-1170
Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial intelligence, Hyperparameter Optimization, Generalization, 02 engineering and technology, Mathematical analysis, Learning with Noisy Labels in Machine Learning, Machine Learning (cs.LG), Artificial Intelligence, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, Active Learning in Machine Learning Research, Constraint Handling, Global Optimization, Optimization Applications, Computer science, Programming language, Automated Machine Learning, Algorithm, Combinatorics, Computer Science, Physical Sciences, Tree (set theory), Pipeline (software), Mathematics
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Autoren: et al.
Weitere Verfasser: et al.
Quelle: J Stat Theory Appl
Schlagwörter: 0301 basic medicine, Artificial intelligence, causality, Explainable Artificial Intelligence, Review, 01 natural sciences, Learning with Noisy Labels in Machine Learning, 03 medical and health sciences, Inference, Artificial Intelligence, Computer security, Machine learning, Interpretability, 0101 mathematics, Model Interpretability, Key (lock), Active Learning in Machine Learning Research, Visualization, inference, predictive statistics, Responsibility in AI, Computer science, Machine Learning Interpretability, Process (computing), Programming language, machine learning, Computer Science, Physical Sciences, Interpretable Models, Robust Learning, Workbench
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Autoren: Aouatef, Mahani
Quelle: Information Systems Management ISBN: 9781803556512
Information Systems ManagementSchlagwörter: FOS: Computer and information sciences, Artificial intelligence, Class (philosophy), Economics, Multi-label classification, Pattern recognition (psychology), Computer science, Detection and Prevention of Phishing Attacks, Management, Task (project management), Artificial Intelligence, Categorization, Multi-label Text Classification in Machine Learning, Computer Science, Physical Sciences, Machine learning, Text categorization, Multi-label Learning, Active Learning in Machine Learning Research, Data mining, Information Systems
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Autoren: et al.
Quelle: Sci Rep
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)Schlagwörter: Pooling, Artificial intelligence, Explainable Artificial Intelligence, Developing country, Economics, Developmental psychology, Semi-Supervised Learning, Low and middle income countries, FOS: Political science, Social Sciences, Machine Learning, Psychology, Equity (law), Business, Model Interpretability, 10. No inequality, Political science, Algorithmic Bias, 1. No poverty, FOS: Philosophy, ethics and religion, 3. Good health, FOS: Psychology, Vietnam, Physical Sciences, 8. Economic growth, Income, Medicine, Interpretable Models, Safety Research, Algorithms, Science, Generalizability theory, Health Informatics, Vietnamese, FOS: Law, Article, FOS: Economics and business, Bias, Artificial Intelligence, Capability Approach, Health Sciences, Machine learning, Humans, Econometrics, Developing Countries, Active Learning in Machine Learning Research, Economic growth, Artificial Intelligence in Medicine, SARS-CoV-2, Developed Countries, Ethical Implications of Artificial Intelligence, COVID-19, Linguistics, Computer science, United Kingdom, Philosophy, Computer Science, FOS: Languages and literature, Law
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Autoren: et al.
Quelle: APL Machine Learning, Vol 1, Iss 4, Pp 046118-046118-10 (2023)
Schlagwörter: 0301 basic medicine, Artificial intelligence, QC1-999, Semi-Supervised Learning, Robustness (evolution), Handling Imbalanced Data in Classification Problems, 02 engineering and technology, Pattern recognition (psychology), Biochemistry, Gene, Learning with Noisy Labels in Machine Learning, 03 medical and health sciences, Artificial Intelligence, Meta-Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Active Learning in Machine Learning Research, Data mining, Curse of dimensionality, Cost-Sensitive Learning, Imbalanced Data, Physics, 4. Education, QA75.5-76.95, 15. Life on land, Computer science, Dimensionality reduction, Algorithm, Chemistry, Electronic computers. Computer science, Computer Science, Physical Sciences, Feature selection, Robust Learning
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Autoren:
Quelle: Natl Sci Rev
Schlagwörter: Artificial intelligence, Active Learning, Transformative learning, 02 engineering and technology, Learning with Noisy Labels in Machine Learning, Artificial Intelligence, Machine learning, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Active Learning in Machine Learning Research, Adaptation to Concept Drift in Data Streams, Biology, Ecology, Special Topic: Machine Learning Automation, 9. Industry and infrastructure, Pedagogy, 4. Education, 15. Life on land, Computer science, Adaptability, FOS: Psychology, 13. Climate action, FOS: Biological sciences, Computer Science, Physical Sciences, Robust Learning
Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39007001
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