Dynamic online traffic identification scheme based on data stream clustering algorithm
2011 4th IEEE International Conference on Broadband Network and Multimedia Technology, 2011Although researches on network traffic identification have already got some achievements, but most of them are not suitable for online traffic classification by considered the dynamic feature of flows. In this paper, we propose a dynamic online traffic identification method by introducing density-based clustering algorithm for stream data called ...
Dan Li +3 more
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Semi-supervised Learning Algorithm for Online Electricity Data Streams
2014Recent developments in electricity market deregulation, the prices are not fixed. In such application, class labels are not available directly and potentially valuable information is lost. A learning model of electricity demand and prices needs to be adaptive for dynamic changes in massive data streams. This paper presents adaptive building of learning
Pramod Patil +2 more
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Implementing Online Viterbi Algorithm as Standard Relational Queries over Streaming Data
Advanced Materials Research, 2012In this paper, we discuss a method for implementing online Viterbi algorithm as standard relational queries over streaming data. Our primary contribution is an approach to storing and manipulating most probable state paths, the candidate solutions to the problem, within a relational data model.
Rui Li, Lei Zhang
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Rival Learner Algorithm with Drift Adaptation for Online Data Stream Regression
Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence, 2018Real-time extraction of meaningful data streams patterns is an increasingly important issue for machine learning and data mining communities. In this paper, we proposed a regression algorithm incremental on data streams which are infinite, high-speed and time-varying. The algorithm integrates two incremental model trees, global and local models.
Zhenwei Liao, Yongheng Wang
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An Online Anomalous Time Series Detection Algorithm for Univariate Data Streams
2013We address the online anomalous time series detection problem among a set of series, combining three simple distance measures. This approach, akin to control charts, makes it easy to determine when a series begins to differ from other series. Empirical evidence shows that this novel online anomalous time series detection algorithm performs very well ...
Huaming Huang +2 more
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Feature-based Online Segmentation Algorithm for Streaming Time Series (Short Paper)
2019Over the last decade, huge number of time series stream data are continuously being produced in diverse fields, including finance, signal processing, industry, astronomy and so on. Since time series data has high-dimensional, real-valued, continuous and other related properties, it is of great importance to do dimensionality reduction as a preliminary ...
Peng Zhan +5 more
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Noisy intermediate-scale quantum algorithms
Reviews of Modern Physics, 2022Kishor Bharti +2 more
exaly
RHDOFS: A Distributed Online Algorithm Towards Scalable Streaming Feature Selection
IEEE Transactions on Parallel and Distributed Systems, 2023Chuan Luo +5 more
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Novel Online Censoring Based Learning Algorithm For Complex-Valued Big Data Streams
2022 30th Signal Processing and Communications Applications Conference (SIU), 2022Çolak Güvenç, Buket +2 more
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Quantum Information and Algorithms for Correlated Quantum Matter
Chemical Reviews, 2021Kade Head-Marsden +2 more
exaly