Results 11 to 20 of about 23,984,354 (259)
Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly [PDF]
Entropy, 2021 When confronted with massive data streams, summarizing data with dimension reduction methods such as PCA raises theoretical and algorithmic pitfalls.
Le Li, Benjamin Guedj
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A Quality Control Methodology for Heterogeneous Vehicular Data Streams [PDF]
Sensors, 2022 The rapid evolution of sensors and communication technologies has led to the production and transfer of mass data streams from vehicles either inside their electronic units or to the outside world using the internet infrastructure.
Konstantina Remoundou +4 more
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IEEE Access, 2021 The Internet of Things (IoT) is constantly growing, generating an uninterrupted data stream pipeline to monitor physical world information. Hence, Artificial Intelligence (AI) continuously evolves, improving life quality and business and academic ...
Alejandro Carnero +5 more
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Continual Learning Approach for Continuous Data Stream Analysis in Dynamic Environments
Applied Sciences, 2023 Continuous data stream analysis primarily focuses on the unanticipated changes in the transmission of data distribution over time. Conceptual change is defined as the signal distribution changes over the transmission of continuous data streams.
K. Prasanna +6 more
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Anomaly Detection on Data Streams for Smart Agriculture
Agriculture, 2021 Smart agriculture technologies are effective instruments for increasing farm sustainability and production. They generate many spatial, temporal, and time-series data streams that, when analysed, can reveal several issues on farm productivity and ...
Juliet Chebet Moso +4 more
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Entropy, 2020 In the era of a large number of tools and applications that constantly produce massive amounts of data, their processing and proper classification is becoming both increasingly hard and important.
Weronika Wegier, Pawel Ksieniewicz
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IEEE Access, 2020 Validation is one of the most important aspects of clustering, particularly when the user is designing a trustworthy or explainable system. However, most clustering validation approaches require batch calculation.
Leonardo Enzo Brito Da Silva +2 more
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An Approximate L^p Difference Algorithm for Massive Data Streams [PDF]
Discrete Mathematics & Theoretical Computer Science, 2001 Several recent papers have shown how to approximate the difference ∑ _i|a_i-b_i| or ∑ |a_i-b_i|^2 between two functions, when the function values a_i and b_i are given in a data stream, and their order is chosen by an adversary.
Jessica H. Fong, Martin Strauss
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Adaptive Regression Analysis of Heterogeneous Data Streams via Models with Dynamic Effects
Mathematics, 2023 Streaming data sequences arise from various areas in the era of big data, and it is challenging to explore efficient online models that adapt to them. To address the potential heterogeneity, we introduce a new online estimation procedure to analyze the ...
Jianfeng Wei +4 more
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Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R
Journal of Statistical Software, 2017 In recent years, data streams have become an increasingly important area of research for the computer science, database and statistics communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non ...
Michael Hahsler +2 more
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