Data stream analysis: Foundations, major tasks and tools
The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social
networks, along with the evolution of technology in different domains, lead to a rise in the …
networks, along with the evolution of technology in different domains, lead to a rise in the …
Fog-DeepStream: A new approach combining LSTM and Concept Drift for data stream analytics on Fog computing
Applications and infrastructures designed to support Fog Computing in IoT (Internet of
Things) environments generate large volumes of data, usually characterized as open-ended …
Things) environments generate large volumes of data, usually characterized as open-ended …
Self-improving generative artificial neural network for pseudorehearsal incremental class learning
Deep learning models are part of the family of artificial neural networks and, as such, they
suffer catastrophic interference when learning sequentially. In addition, the greater number …
suffer catastrophic interference when learning sequentially. In addition, the greater number …
[HTML][HTML] Online learning and continuous model upgrading with data streams through the Kafka-ML framework
A pipeline of constant data streams is being built by the Internet of Things (IoT) to monitor
information about the physical environment. In parallel, Artificial Intelligence (AI) is …
information about the physical environment. In parallel, Artificial Intelligence (AI) is …
Incremental learning model inspired in rehearsal for deep convolutional networks
Abstract In Deep Learning, training a model properly with a high quantity and quality of data
is crucial in order to achieve a good performance. In some tasks, however, the necessary …
is crucial in order to achieve a good performance. In some tasks, however, the necessary …
Mitigating catastrophic forgetting in deep learning in a streaming setting using historical summary
Recent advancements in scientific equipment and the adaptation of electronics and the
Internet of Things (IoT) in our everyday lives resulted in large and complex data production …
Internet of Things (IoT) in our everyday lives resulted in large and complex data production …
Online machine learning-based predictive maintenance for the railway industry
MH Le Nguyen - 2023 - theses.hal.science
Being an effective long-distance mass transit, the railway will continue to flourish for its
limited carbon footprint in the environment. Ensuring the equipment's reliability and …
limited carbon footprint in the environment. Ensuring the equipment's reliability and …
Poster: StreamToxWatch–Data Poisoning Detector in Distributed, Event-based Environments
E Begoli - Proceedings of the 17th ACM International Conference …, 2023 - dl.acm.org
StreamToxWatch, or ToxWatch for short, is an early-stage ensemble architecture for data
poisoning detection and monitoring in online learning systems over streams. Detecting data …
poisoning detection and monitoring in online learning systems over streams. Detecting data …
Deep online classification using pseudo-generative models
A Besedin, P Blanchart, M Crucianu… - Computer Vision and …, 2020 - Elsevier
In this work we propose a new deep learning based approach for online classification on
streams of high-dimensional data. While requiring very little historical data storage, our …
streams of high-dimensional data. While requiring very little historical data storage, our …
Online learning and continuous model upgrading with data streams through the Kafka-ML framework
A Carnero Hijano, C Martín-Fernández, G Jeon… - 2024 - riuma.uma.es
A pipeline of constant data streams is being built by the Internet of Things (IoT) to monitor
information about the physical environment. In parallel, Artificial Intelligence (AI) is …
information about the physical environment. In parallel, Artificial Intelligence (AI) is …