Search Results - Computing methodologies Machine learning Machine learning approaches Stochastic games*

Information maximization for a broad variety of multi-armed bandit games

Authors: Barbier--Chebbah, Alex Vestergaard, Christian, L. Masson, Jean-Baptiste et al.

Contributors: Barbier--Chebbah, Alex Vestergaard, Christian, L. Masson, Jean-Baptiste et al.

Source: https://pasteur.hal.science/pasteur-04997815 ; 2025.

Subject Terms: Statistical Inference, Infomax, Multi-armed Bandit, Decision and information theory, Exploration-exploitation, 02.50.Tt89.70.+c, MESH: Decision Theory Information Theory, MESH: Information Theory, MESH: Algorithms, JEL: C - Mathematical and Quantitative Methods/C.C7 - Game Theory and Bargaining Theory/C.C7.C73 - Stochastic and Dynamic Games • Evolutionary Games • Repeated Games, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.2: Approximation/G.1.2.6: Minimax approximation and algorithms, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Availability: https://pasteur.hal.science/pasteur-04997815
https://pasteur.hal.science/pasteur-04997815v1/document
https://pasteur.hal.science/pasteur-04997815v1/file/Information%20maximization%20for%20a%20broad%20variety%20of%20multi-armed%20bandit%20games.pdf

RAVE-HD: A Novel Sequential Deep Learning Approach for Heart Disease Risk Prediction in e-Healthcare.

Authors: Khan, Muhammad Jaffar Raza, Basit Faheem, Muhammad

Source: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 22, p2866, 50p

Subject Terms: HEART diseases, DEEP learning, MEDICAL screening, FEATURE selection, MACHINE learning, PREDICTION models, DIGITAL health, STATISTICAL bias

A multimodal approach to psychological resilience prediction in football players: Integrating biomechanical analysis, physiological feedback, and machine learning.

Authors: Wu, Chen

Source: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 5, p1-16, 16p

Subject Terms: PSYCHOLOGICAL resilience, BIOMECHANICS, PREDICTION models, SOCCER players, MATHEMATICAL optimization, PHYSIOLOGY, STRESS management, MACHINE learning

Predicting the Landscape Epidemiology of Foot-and-Mouth Disease in Endemic Regions: An Interpretable Machine Learning Approach.

Authors: Alkhamis, Moh A. Abouelhassan, Hamad Alateeqi, Abdulaziz et al.

Source: Viruses (1999-4915); Oct2025, Vol. 17 Issue 10, p1383, 20p

Subject Terms: FOOT & mouth disease, EPIDEMIOLOGY, LANDSCAPES, RISK assessment, ANIMAL health, MACHINE learning, PREDICTION models

Geographic Terms: MIDDLE East, ARABIAN Peninsula

Virtual reality-assisted visualization of flood susceptibility using optimized machine learning models.

Authors: Razavi-Termeh, Seyed Vahid Safari Bazargani, Jalal Sadeghi-Niaraki, Abolghasem et al.

Source: Applied Water Science; Oct2025, Vol. 15 Issue 10, p1-21, 21p

Subject Terms: VIRTUAL reality, MACHINE learning, OPTIMIZATION algorithms, FLOOD risk, ENVIRONMENTAL mapping, GEOGRAPHICAL positions, RANDOM forest algorithms

Geographic Terms: FARS (Iran)

Unravelling emotions: exploring deep learning approaches for EEG-based emotion recognition with current challenges and future recommendations.

Authors: Abgeena, Abgeena Garg, Shruti

Source: Cognitive Neurodynamics; 10/23/2025, Vol. 19 Issue 1, p1-32, 32p

Machine Learning for Basketball Game Outcomes: NBA and WNBA Leagues.

Authors: Alves, João M. Barbosa, Ramiro S.

Source: Computation; Oct2025, Vol. 13 Issue 10, p230, 31p

Subject Terms: MACHINE learning, BASKETBALL, FORECASTING, ARTIFICIAL intelligence, WOMEN'S basketball, DEEP learning, ECONOMIC competition

Company/Entity: WOMEN'S National Basketball Association, NATIONAL Basketball Association

Capturing the complexity of human strategic decision-making with machine learning.

Authors: Zhu, Jian-Qiao Peterson, Joshua C. Enke, Benjamin et al.

Source: Nature Human Behaviour; Oct2025, Vol. 9 Issue 10, p2114-2120, 7p

Intelligent Real-Time Fitness Observation System Using IoT and Deep Learning.

Authors: kiran, Kasi Venkata Rao, T. Srinivasa

Source: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 3, p2651-2665, 15p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, ATHLETES' health, DEEP learning, WOUNDS & injuries

Different Time-Increment Rainfall Prediction Models: a Machine Learning Approach Using Various Input Scenarios.

Authors: Rahimi, Anas Yashooa, Noor Kh. Ahmed, Ali Najah et al.

Source: Water Resources Management; Mar2025, Vol. 39 Issue 4, p1677-1696, 20p

Subject Terms: WATER management, MACHINE learning, FLOOD forecasting, METEOROLOGICAL stations, ARTIFICIAL intelligence

Geographic Terms: MALAYSIA

Data-driven predictive modeling of PM 2.5 concentrations using machine learning and deep learning techniques: a case study of Delhi, India.

Authors: Masood A Ahmad K

Source: Environmental monitoring and assessment [Environ Monit Assess] 2022 Nov 03; Vol. 195 (1), pp. 60. Date of Electronic Publication: 2022 Nov 03.

Publication Type: Journal Article

Journal Info: Publisher: Springer Country of Publication: Netherlands NLM ID: 8508350 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2959 (Electronic) Linking ISSN: 01676369 NLM ISO Abbreviation: Environ Monit Assess Subsets: MEDLINE

MeSH Terms: Deep Learning* , Air Pollutants*/analysis , Air Pollution*/analysis, Benzene/analysis ; Environmental Monitoring/methods ; Machine Learning ; Particulate Matter/analysis

An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data.

Authors: Zhao H Miao C Zhu Y et al.

Source: BMC cancer [BMC Cancer] 2025 Jul 16; Vol. 25 (1), pp. 1178. Date of Electronic Publication: 2025 Jul 16.

Publication Type: Journal Article

Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100967800 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2407 (Electronic) Linking ISSN: 14712407 NLM ISO Abbreviation: BMC Cancer Subsets: MEDLINE

MeSH Terms: Gallbladder Neoplasms*/diagnosis , Gallbladder Neoplasms*/diagnostic imaging , Gallbladder Neoplasms*/pathology , Machine Learning* , Early Detection of Cancer*/methods , Multimodal Imaging*/methods, Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Aged ; Tomography, X-Ray Computed ; Adult ; Sensitivity and Specificity ; Neoplasm Staging

Deep reinforcement learning-driven personalized training load control algorithm for competitive sports performance optimization.

Authors: Xia X Chen Q Wang Z

Source: Scientific reports [Sci Rep] 2025 Dec 01. Date of Electronic Publication: 2025 Dec 01.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts.

Authors: Zhao, Yuan Paul, Ronak Reid, Sean et al.

Source: Social Indicators Research; Nov2024, Vol. 175 Issue 2, p639-657, 19p

Subject Terms: PRINCIPAL components analysis, DEEP learning, MACHINE learning, ECONOMIC status, NATURAL disasters

Effect of natural and synthetic noise data augmentation on physical action classification by brain–computer interface and deep learning.

Authors: Gordienko, Yuri Gordienko, Nikita Taran, Vladyslav et al.

Source: Frontiers in Neuroinformatics; 2025, p1-25, 25p

Subject Terms: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, DATA augmentation, COMMUNICATION infrastructure, BRAIN-computer interfaces, DEEP learning

Distributed Learning in Hierarchical Networks

Authors: Le Cadre, Hélène Bedo, Jean-Sébastien Laboratoire Information, Modèles, Apprentissage (CEA, LIST) (LIMA (CEA, LIST)) et al.

Contributors: Le Cadre, Hélène Bedo, Jean-Sébastien Laboratoire Information, Modèles, Apprentissage (CEA, LIST) (LIMA (CEA, LIST)) et al.

Source: 6th International ICST Conference on Performance Evaluation Methodologies and Tools (ValueTools 2012)
https://hal.science/hal-00740905
6th International ICST Conference on Performance Evaluation Methodologies and Tools (ValueTools 2012), Oct 2012, Cargèse, France. http://valuetools.org/2012/show/home, ⟨10.4108/valuetools.2012.250217⟩

Subject Terms: online learning, Distributed Learning, Coalition, Algorithmic Game Theory, machine learning, control engineering computing, hierarchical systems, optimal control, Regret, power system control, power system management, renewable energy sources, smart power grid, smart grid, smart grid management, optimal control strategy, competitive learning algorithm, energy forecasting, artificial intelligence, power engineering computing, distributed learning approach, decentralized hierarchical network system, nonrenewable energy production control, renewable energy integration control, JEL: E - Macroeconomics and Monetary Economics/E.E3 - Prices, Business Fluctuations, and Cycles/E.E3.E37 - Forecasting and Simulation: Models and Applications, JEL: C - Mathematical and Quantitative Methods/C.C7 - Game Theory and Bargaining Theory/C.C7.C73 - Stochastic and Dynamic Games • Evolutionary Games • Repeated Games, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], [QFIN.PR]Quantitative Finance [q-fin]/Pricing of Securities [q-fin.PR]

Subject Geographic: Cargèse, France

Availability: https://hal.science/hal-00740905
https://hal.science/hal-00740905v1/document
https://hal.science/hal-00740905v1/file/sigproc-sp_js_vf.pdf
https://doi.org/10.4108/valuetools.2012.250217

A Machine Learning Approach to Classifying EEG Data Collected with or without Haptic Feedback during a Simulated Drilling Task.

Authors: Ramirez Campos, Michael S. McCracken, Heather S. Uribe-Quevedo, Alvaro et al.

Source: Brain Sciences (2076-3425); Sep2024, Vol. 14 Issue 9, p894, 15p

Subject Terms: FEATURE selection, ARTIFICIAL intelligence, MACHINE learning, NEURAL circuitry, VIRTUAL reality

A Novel Optimized Hybrid Deep Learning Framework for Mental Stress Detection Using Electroencephalography.

Authors: Andhare, Maithili Shailesh Vijayan, T. Karthik, B. et al.

Source: Brain Sciences (2076-3425); Aug2025, Vol. 15 Issue 8, p835, 27p

Subject Terms: PSYCHOLOGICAL stress, DEEP learning, RESEARCH evaluation, ELECTROENCEPHALOGRAPHY, OPTIMIZATION algorithms, FEATURE selection

Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.

Authors: Onciul, Razvan Tataru, Catalina-Ioana Dumitru, Adrian Vasile et al.

Source: Journal of Clinical Medicine; Jan2025, Vol. 14 Issue 2, p550, 45p

Subject Terms: MACHINE learning, ARTIFICIAL intelligence, SIGNAL processing, BRAIN research, DATA integration

Simulating Subjects: The Promise and Peril of Artificial Intelligence Stand-Ins for Social Agents and Interactions.

Authors: Kozlowski, Austin C. Evans, James

Source: Sociological Methods & Research; Aug2025, Vol. 54 Issue 3, p1017-1073, 57p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, LANGUAGE models, GENERATIVE artificial intelligence, COMPUTATIONAL intelligence