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Keyword

stream learning

Description: Stream learning is a machine-learning approach that updates models from continuous, potentially unbounded streams of data as records arrive.
Wikidata ID: wiki/Q3079880
OpenAlex ID: keywords/stream-learning
On evaluating stream learning algorithms
2012 · João Gama, Raquel Sebastião, et al. · Machine Learning · 534
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Issues in evaluation of stream learning algorithms
2009 · João Gama, Raquel Sebastião, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 338
Scikit-Multiflow: A Multi-output Streaming Framework
2018 · Montiel, Jacob, Read, Jesse, et al. · arXiv (Cornell University) · 285
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River: Machine learning for streaming data in python
2020 · Montiel, J, Halford, M, et al. · arXiv (Cornell University) · 209
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Synaptic metaplasticity in binarized neural networks
2021 · Axel Laborieux, Maxence Ernoult, et al. · Nature Communications · 85
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Methods for Incremental Learning : A Survey
2013 · Ade R.R, Deshmukh P. R · International Journal of Data Mining & Knowledge Management Process · 81
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Self-adaptive and local strategies for a smooth treatment of drifts in data streams
2014 · Ammar Shaker, Edwin Lughofer · Evolving Systems · 68
Mining complex models from arbitrarily large databases in constant time
2002 · Geoff Hulten, Pedro Domingos · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 65
Synaptic metaplasticity in binarized neural networks
· Axel Laborieux, Maxence Ernoult, et al. · RePEc: Research Papers in Economics · 63
A new approach for crude oil price prediction based on stream learning
2016 · Shuang Gao, Yalin Lei · Geoscience Frontiers · 61
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A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems
2022 · Ehsan Hallaji, Roozbeh Razavi-Far, et al. · IEEE Transactions on Information Forensics and Security · 52
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Survey on Online Streaming Continual Learning
2023 · Nuwan Gunasekara, Bernhard Pfahringer, et al. · International Joint Conference on Artificial Intelligence · 43
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Cost-sensitive continuous ensemble kernel learning for imbalanced data streams with concept drift
2023 · Yingying Chen, Xiaowei Yang, et al. · Knowledge-Based Systems · 35
Toward feasible machine learning model updates in network-based intrusion detection
2021 · Pedro Horchulhack, Eduardo K. Viegas, et al. · Computer Networks · 33
Online Machine Learning in Big Data Streams: Overview
2018 · András A. Benczúr, Levente Kocsis, et al. · Encyclopedia of Big Data Technologies · 29
Identifying and using patterns in sequential data
1993 · Philip Laird · Lecture notes in computer science · 28
Improved Feature Selection and Stream Traffic Classification Based on Machine Learning in Software-Defined Networks
2024 · Arwa M. Eldhai, Mosab Hamdan, et al. · IEEE Access · 22
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$$\mathsf {FABBOO}$$ - Online Fairness-Aware Learning Under Class Imbalance
2020 · Vasileios Iosifidis, Eirini Ntoutsi · Lecture notes in computer science · 20
A Resilient Stream Learning Intrusion Detection Mechanism for Real-Time Analysis of Network Traffic
2017 · Eduardo Viegas, Altair Santin, et al. · Globecom · 20
Camel: Managing Data for Efficient Stream Learning
2022 · Yiming Li, Yanyan Shen, et al. · Proceedings - ACM-SIGMOD International Conference on Management of Data · 19
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams
2019 · Kachuee, Mohammad, Goldstein, Orpaz, et al. · arXiv (Cornell University) · 19
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IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning
2020 · Communications in computer and information science · 18
Stream learning and anomaly-based intrusion detection in the adversarial settings
2017 · Eduardo Viegas, Altair Santin, et al. · Proceedings - IEEE Symposium on Computers and Communications/IEEE Symposium on Computers and Communications · 17
Scikit-Multiflow: A Multi-output Streaming Framework
2018 · Montiel, Jacob, Read, Jesse, et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 16
Stream Learning in Energy IoT Systems: A Case Study in Combined Cycle Power Plants
2020 · Jesus L. Lobo, Igor Ballesteros, et al. · Energies · 15
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Works count: 181
Citation count: 2,563
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