Improving Causality Induction with Category Learning by Yi Guo, Zhihong Wang, Zhiqing Shao

“…This paper confirms the expectation that the precision and coverage of causality induction can be remarkably improved by means of causal and category learning.…”
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Identifying Transfer Learning in the Reshaping of Inductive Biases by Anna Székely, Balázs Török, Mariann Kiss, Karolina Janacsek, Dezső Németh, Gergő Orbán

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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…This research study centers on the development of a versatile machine-learning model for predicting faults in induction motors within industrial environments. …”
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ILA4: Overcoming missing values in machine learning datasets – An inductive learning approach by Ammar Elhassan, Saleh M. Abu-Soud, Firas Alghanim, Walid Salameh

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Coordinate Representations for Interference Reduction in Motor Learning. by Sang-Hoon Yeo, Daniel M Wolpert, David W Franklin

“…However, any difference in the limb's endpoint location typically changes the hand position, joint angles and the hand orientation making it ambiguous as to which of these changes underlies the ability to learn dynamics that normally interfere. Here we examine the extent to which each of these three possible coordinate systems--Cartesian hand position, shoulder and elbow joint angles, or hand orientation--underlies the reduction in interference. …”
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Research on Vibration Reduction Control Based on Reinforcement Learning by Rongyao Yuan, Yang Yang, Chao Su, Shaopei Hu, Heng Zhang, Enhua Cao

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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…Our findings underscore the effective use of unsupervised learning approaches in test suite reduction.…”
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Fatigue damage reduction in hydropower startups with machine learning by Till Muser, Ekaterina Krymova, Alessandro Morabito, Martin Seydoux, Elena Vagnoni

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OntoLearn Reloaded: A Graph-Based Algorithm for Taxonomy Induction by Paola Velardi, Stefano Faralli, Roberto Navigli

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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

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Transfer Learning for Induction Motor Health Monitoring: A Brief Review by Prashant Kumar

“…These sophisticated deep learning algorithms have been widely used for induction motor health monitoring due to their autonomous feature extraction abilities and end-to-end learning capabilities. …”
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Model-Based Graph Reinforcement Learning for Inductive Traffic Signal Control by Francois-Xavier Devailly, Denis Larocque, Laurent Charlin

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Explainability in RIONA Algorithm Combining Rule Induction and Instance-Based Learning by Grzegorz Góra, Andrzej Skowron, Arkadiusz Wojna

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Induction of Convolutional Decision Trees for Semantic Segmentation of Color Images Using Differential Evolution and Time and Memory Reduction Techniques by Adriana-Laura López-Lobato, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes

“…Convolutional Decision Trees (CDTs) are machine learning models utilized as interpretable methods for image segmentation. …”
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Reduction of monoclonal antibody viscosity using interpretable machine learning by Emily K. Makowski, Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock, Patrick Underhill, Emma Pelegri-O’Day, Erick Maglalang, Dwight Winters, Peter M. Tessier

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Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning by Matt von Hippel, Matthias Wilhelm

“…Abstract Integration-by-parts reductions of Feynman integrals pose a frequent bottleneck in state-of-the-art calculations in theoretical particle and gravitational-wave physics, and rely on heuristic approaches for selecting integration-by-parts identities, whose quality heavily influences the performance. …”
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Digital intelligence and synergy of pollution reduction and carbon reduction: “Dividend” or “gap”? by Jiajia Li, Xianfeng Han, Tonglei Zhang, Jian Xiao, Longtao Chen

Subjects: “…Synergy of pollution reduction and carbon reduction…”
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Privacy-Preserving Rule Induction Using CKKS by Jihyeon Choi, Jina Choi, Younho Lee, Jung-Sik Hong

Subjects: “…Rule induction…”
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Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction. by Xianghao Zhan, Qinmei Xu, Yuanning Zheng, Guangming Lu, Olivier Gevaert

“…Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. …”
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Induction of gender-like linguistic categories using noun-marking and blocking of learning trials by Roman Taraban

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