Results 21 to 30 of about 23,720,719 (291)
Dynamic Data Sample Selection and Scheduling in Edge Federated Learning
IEEE Open Journal of the Communications Society, 2023 Federated Learning (FL) is a state-of-the-art paradigm used in Edge Computing (EC). It enables distributed learning to train on cross-device data, achieving efficient performance, and ensuring data privacy. In the era of Big Data, the Internet of Things (
Mohamed Adel Serhani +5 more
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Adaptive Real-Time Method for Anomaly Detection Using Machine Learning
Proceedings, 2020 Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring and the lack of methods capable of learning ...
David Novoa-Paradela +2 more
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Proceedings of the 9th International Conference on Cloud Computing and Services Science, 2019 Nowadays many applications require to analyse the continuous flow of data produced by different data sources before the data is stored. Data streaming engines emerged as a solution for processing data on the fly. At the same time, computer architectures have evolved to systems with several interconnected CPUs and Non Uniform Memory Access (NUMA), where
Patiño Martínez, Marta +1 more
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Parameterized streaming : maximal matching and vertex cover [PDF]
, 2014 As graphs continue to grow in size, we seek ways to effectively process such data at scale. The model of streaming graph processing, in which a compact summary is maintained as each edge insertion/deletion is observed, is an attractive one.
Chitnis, Rajesh; id_orcid +11 more
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2011 Data Compression Conference, 2011 We present a general-purpose, loss less compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the inference procedure used in the probabilistic model underpinning deplump are introduced that yield the computational asyptotics necessary for stream compression. We demonstrate the
Bartlett, N, Wood, F
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ISPRS International Journal of Geo-Information, 2018 There is an increasing impetus for the use of digital city models and sensor network data to understand the current demand for utility resources and inform future infrastructure service planning across a range of spatial scales.
Thomas Gilbert +4 more
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Research World, 2016 Big Data is top of mind in many organisations because of the flood of data now available. There is a belief that analysing Big Data can bring substantial competitive advantages. However collecting and storing the massive data streams‒although a challenge in itself‒is only part of the story.
Kooge, Edwin +2 more
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HYBRID APPROACH FOR DATA FILTERING AND MACHINE LEARNING INSIDE CONTENT MANAGEMENT SYSTEM
Сучасні інформаційні системи, 2023 The object of research is the processes of data filtering and machine learning in content management systems. The subject of research is developing a hybrid approach to data filtering based on a combination of supervised and unsupervised machine ...
Oleh Poliarush +2 more
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Improvement of Kafka Streaming Using Partition and Multi-Threading in Big Data Environment
Sensors, 2019 The large amount of programmable logic controller (PLC) sensing data has rapidly increased in the manufacturing environment. Therefore, a large data store is necessary for Big Data platforms.
Bunrong Leang +3 more
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A QFT Approach to Data Streaming in Natural and Artificial Neural Networks
Proceedings, 2021 In the actual panorama of machine learning (ML) algorithms, the issue of the real-time information extraction/classification/manipulation/analysis of data streams (DS) is acquiring an ever-growing relevance. They arrive generally at high speed and always
Gianfranco Basti, Giuseppe Vitiello
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