Search Results - meta-learning. articles swart optimization. genetics programming. algorithm generation.

Improving Variable Orderings of Approximate Decision Diagrams Using Reinforcement Learning.

Authors: Cappart, Quentin Bergman, David Rousseau, Louis-Martin et al.

Source: INFORMS Journal on Computing; Sep/Oct2022, Vol. 34 Issue 5, p2552-2570, 19p

Subject Terms: REINFORCEMENT learning, MACHINE learning, LINEAR programming, INDEPENDENT sets

Intentional change, intrinsic motivations, and goal generation.

Authors: Manzotti, Riccardo Moderato, Paolo

Source: Behavioral & Brain Sciences; Aug2014, Vol. 37 Issue 4, p431-432, 2p

Subject Terms: MOTIVATION (Psychology), SOCIAL change, MACHINE learning, ARTIFICIAL intelligence, SOCIAL sciences, METACOGNITION

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

Authors: Miannay, Bertrand Minvielle, Stéphane Magrangeas, Florence et al.

Source: BMC Systems Biology; 3/21/2018, Vol. 12 Issue Suppl 3, p1-1, 1p

Subject Terms: MULTIPLE myeloma, GENE expression profiling, GRAPH theory, CELL communication, LOGIC programming, GENETICS

Catecholaminergic modulation of meta-learning

Authors: Dirk E. M. Geurts Jennifer Cook Hanneke E. M. den Ouden et al.

Contributors: Dirk E. M. Geurts Jennifer Cook Hanneke E. M. den Ouden et al.

Source: eLife
eLife, Vol 8 (2019)
Elife, 8

Subject Terms: Adult, Male, 0301 basic medicine, Adolescent, QH301-705.5, Science, Dopamine, volatility, Radboud University Medical Center, 610 Medicine & health, Genetics and Molecular Biology, methylphenidate, 170 Ethics, Radboudumc 13: Stress-related disorders DCMN: Donders Center for Medical Neuroscience, Placebos, Norepinephrine, Young Adult, 03 medical and health sciences, meta-learning, Dopamine Uptake Inhibitors, 1300 General Biochemistry, Genetics and Molecular Biology, 2400 General Immunology and Microbiology, Humans, Learning, 10237 Institute of Biomedical Engineering, learning rate, Biology (General), 2. Zero hunger, 0303 health sciences, Neuro- en revalidatiepsychologie, General Immunology and Microbiology, General Neuroscience, Neuropsychology and rehabilitation psychology, 2800 General Neuroscience, General Medicine, 16. Peace & justice, General Biochemistry, noradrenaline, Methylphenidate, Medicine, Female, dopamine, 170 000 Motivational & Cognitive Control, Neuroscience

File Description: 2019_elife-51439-v2.pdf - application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/31850844
https://doaj.org/article/3595c7cbfb774e99ad570fdbf7453334
https://pubmed.ncbi.nlm.nih.gov/31850844/
https://osf.io/z59us/#!
https://repository.ubn.ru.nl/handle/2066/215394
https://www.zora.uzh.ch/id/eprint/183319/
https://www.zora.uzh.ch/id/eprint/183319/1/2019_elife-51439-v2.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974360
https://repository.ubn.ru.nl//bitstream/handle/2066/215394/215394.pdf
https://hdl.handle.net/2066/215394

Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study.

Authors: GEMEINHARDT, FELIX GARMENDIA, ANTONIO WIMMER, MANUEL et al.

Source: ACM Computing Surveys; Mar2024, Vol. 56 Issue 3, p1-36, 36p

Subject Terms: SCIENCE education, SCIENTIFIC literature, QUANTUM annealing, QUADRATIC assignment problem, OPTIMIZATION algorithms, QUANTUM computers, TABU search algorithm

Innovative Integration of Q-learning in BSO Algorithm for Adaptive Community Detection in Social Networks.

Authors: Beldi, Zohra Bessedik, Malika

Source: ACM Transactions on the Web; May2025, Vol. 19 Issue 2, p1-34, 34p

Subject Terms: OPTIMIZATION algorithms, SOCIAL network analysis, SOCIAL networks, REINFORCEMENT learning, SOCIAL systems

Application of Reinforcement Learning Methods Combining Graph Neural Networks and Self-Attention Mechanisms in Supply Chain Route Optimization.

Authors: Wang, Yang Liang, Xiaoxiang

Source: Sensors (14248220); Feb2025, Vol. 25 Issue 3, p955, 30p

Subject Terms: GRAPH neural networks, SUPPLY chain management, REINFORCEMENT learning, REPRESENTATIONS of graphs, SUPPLY chains

Catecholaminergic modulation of meta-learning

Authors: Cook, Jennifer L Swart, Jennifer C Froböse, Monja I et al.

Source: Cook, Jennifer L; Swart, Jennifer C; Froböse, Monja I; Diaconescu, Andreea O; Geurts, Dirk E M; den Ouden, Hanneke E M; Cools, Roshan (2019). Catecholaminergic modulation of meta-learning. eLife, 8:e51439.

Subject Terms: Institute of Biomedical Engineering, 170 Ethics, 610 Medicine & health, General Biochemistry, Genetics and Molecular Biology, General Immunology and Microbiology, General Neuroscience, General Medicine, edu, hisphilso

Relation: https://www.zora.uzh.ch/id/eprint/183319/1/2019_elife-51439-v2.pdf; https://www.zora.uzh.ch/id/eprint/183319/

Availability: https://www.zora.uzh.ch/id/eprint/183319/1/2019_elife-51439-v2.pdf
https://www.zora.uzh.ch/id/eprint/183319/

Cognitive Evaluation of Examinees by Dynamic Question Set Generation based on Bloom's Taxonomy.

Authors: Dutta, Anjan Chatterjee, Punyasha Dey, Nilanjan et al.

Source: IETE Journal of Research; Mar2024, Vol. 70 Issue 3, p2570-2582, 13p

Subject Terms: BLOOM'S taxonomy, DATA mining, MACHINE learning, MATHEMATICAL optimization

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy.

Authors: Fleuren, Lucas M. Klausch, Thomas L. T. Zwager, Charlotte L. et al.

Source: Intensive Care Medicine; Mar2020, Vol. 46 Issue 3, p383-400, 18p, 2 Diagrams, 7 Charts, 3 Graphs

Subject Terms: META-analysis, MACHINE learning, SEPSIS, SEPTIC shock, ONLINE information services, MEDICAL information storage & retrieval systems, SYSTEMATIC reviews, MEDLINE

Classical symmetries and the Quantum Approximate Optimization Algorithm.

Authors: Shaydulin, Ruslan Hadfield, Stuart Hogg, Tad et al.

Source: Quantum Information Processing; Nov2021, Vol. 20 Issue 11, p1-28, 28p

Subject Terms: MATHEMATICAL optimization, SYMMETRY, SYMMETRY groups, ALGORITHMS, MACHINE learning, APPROXIMATION algorithms, PROBABILITY theory

Exploring Multiple-Objective Optimization for Efficient and Effective Test Paper Design with Dynamic Programming Guided Genetic Algorithm.

Authors: Wang, Han Zhuge, Qingfeng Sha, Edwin Hsing-Mean et al.

Source: Mathematical Biosciences & Engineering; 2024, Vol. 21 Issue 3, p1-27, 27p

Next-Generation Approaches in Sports Medicine: The Role of Genetics, Omics, and Digital Health in Optimizing Athlete Performance and Longevity—A Narrative Review.

Authors: Juginović, Alen Kekić, Adrijana Aranza, Ivan et al.

Source: Life (2075-1729); Jul2025, Vol. 15 Issue 7, p1023, 22p

Subject Terms: SPORTS medicine, GENETICS, PREVENTION of injury, DIGITAL health, ATHLETIC ability, INDIVIDUALIZED medicine, PHARMACOGENOMICS, MULTIOMICS

Improving Forest Detection Using Machine Learning and Remote Sensing: A Case Study in Southeastern Serbia.

Authors: Potić, Ivan Srdić, Zoran Vakanjac, Boris et al.

Source: Applied Sciences (2076-3417); Jul2023, Vol. 13 Issue 14, p8289, 24p

Subject Terms: MACHINE learning, REMOTE sensing, MULTISPECTRAL imaging, DISTANCE education, VEGETATION monitoring, PYTHON programming language

Geographic Terms: SERBIA

Does evolving the future preclude learning from it?

Authors: Dowrick, Peter W.

Source: Behavioral & Brain Sciences; Aug2014, Vol. 37 Issue 4, p422-423, 2p

Subject Terms: HUMAN behavior, SOCIAL change, SOCIAL learning, PSYCHOLOGICAL feedback, MINDFULNESS

Evolving the future by learning from the future (as it emerges)? Toward an epistemology of change.

Authors: Peschl, Markus F. Fundneider, Thomas

Source: Behavioral & Brain Sciences; Aug2014, Vol. 37 Issue 4, p433-434, 2p

Subject Terms: LEARNING, THEORY of knowledge, TECHNOLOGICAL innovations, ADAPTABILITY (Personality), SENSORY perception, COGNITIVE therapy

Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives.

Authors: Fahim, Yosri A. Hasani, Ibrahim W. Kabba, Samer et al.

Source: European Journal of Medical Research; 9/29/2025, Vol. 30 Issue 1, p1-21, 21p

Subject Terms: ARTIFICIAL intelligence, MACHINE learning, MEDICAL care, CLINICAL medicine, THERAPEUTICS, TREATMENT effectiveness

BuildAMol: a versatile Python toolkit for fragment-based molecular design.

Authors: Kleinschmidt, Noah Lemmin, Thomas

Source: Journal of Cheminformatics; 8/25/2024, Vol. 16 Issue 1, p1-13, 13p

Subject Terms: SOFTWARE development tools, LEARNING curve, DRUG discovery, MOLECULAR structure, MOLECULAR models

Machine and Deep Learning in Agricultural Engineering: A Comprehensive Survey and Meta-Analysis of Techniques, Applications, and Challenges.

Authors: Frimpong, Samuel Akwasi Han, Mu Zheng, Wenyi et al.

Source: Computers (2073-431X); Oct2025, Vol. 14 Issue 10, p438, 33p

Subject Terms: MACHINE learning, DEEP learning, ENVIRONMENTAL monitoring, PRECISION farming, FOOD production, PRODUCT quality, AUTOMATION, AGRICULTURAL engineering

For public policies, our evolved psychology is the problem and the solution.

Authors: Baumard, Nicolas

Source: Behavioral & Brain Sciences; Aug2014, Vol. 37 Issue 4, p418-419, 2p

Subject Terms: GOVERNMENT policy, EVOLUTIONARY psychology, REPUTATION, HUMAN behavior, MOTIVATION (Psychology), SOCIAL learning