Results 21 to 30 of about 10,022,386 (288)
A Multiscale Clustering Approach for Non-IID Nominal Data. [PDF]
Comput Intell Neurosci, 2021 Multiscale brings great benefits for people to observe objects or problems from different perspectives. Multiscale clustering has been widely studied in various disciplines. However, most of the research studies are only for the numerical dataset, which is a lack of research on the clustering of nominal dataset, especially the data are nonindependent ...
Chen R, Zhao S, Tian Z.
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Homophily outlier detection in non-IID categorical data [PDF]
Data Mining and Knowledge Discovery, 2021 To appear in Data Ming and Knowledge Discovery ...
Guansong Pang +2 more
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Non-IID Transfer Learning on Graphs
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 Transfer learning refers to the transfer of knowledge or information from a relevant source domain to a target domain. However, most existing transfer learning theories and algorithms focus on IID tasks, where the source/target samples are assumed to be independent and identically distributed. Very little effort is devoted to theoretically studying the
Jun Wu 0019 +2 more
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FedLC: Optimizing Federated Learning in Non-IID Data via Label-Wise Clustering
IEEE Access, 2023 As contemporary systems are being operated in dynamic situations alternating into decentralized and distributed environments from conventional centralized frameworks, Federated Learning (FL) has been gaining attention for an effective architecture when ...
Hunmin Lee, Daehee Seo
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Federated Learning With Taskonomy for Non-IID Data
IEEE Transactions on Neural Networks and Learning Systems, 2023 Classical federated learning approaches incur significant performance degradation in the presence of non-IID client data. A possible direction to address this issue is forming clusters of clients with roughly IID data. Most solutions following this direction are iterative and relatively slow, also prone to convergence issues in discovering underlying ...
Hadi Jamali Rad +2 more
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Frontiers in Neurology, 2022 ObjectiveTo analyze the interictal discharge (IID) patterns on pre-operative scalp electroencephalogram (EEG) and compare the changes in IID patterns after removal of epileptogenic tubers in preschool children with tuberous sclerosis complex (TSC ...
Liu Yuan +10 more
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Adaptive Federated Learning With Non-IID Data
The Computer Journal, 2022 Abstract With the widespread use of Internet of things(IoT) devices, it generates an enormous volume of data, and it is a challenge to mine the IoT data value while ensuring security and privacy. Federated learning is a decentralized approach for training data located on edge devices, such as mobile phones and IoT devices, while keeping ...
Yan Zeng +7 more
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, 2023 Personalized federated learning simulation platform with non-IID and unbalanced ...
Tsing +3 more
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IID-DTH/2019nCov-iSNV: iSNV_figures
, 2021 R scripts for figures in Two-step fitness selection for intra-host variations in SARS-CoV-
IID-DTH
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, 2023 <p>First version of code for benchmarking normalization layers in federated learning for image classification tasks on non-iid data</p ...
Bruno Casella
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