Albert Bifet

Low-latency multi-threaded ensemble learning for dynamic big data streams

2017

Real-time mining of evolving data streams involves new challenges when targeting today's application domains such as the Internet of the Things: increasing volume, velocity and volatility requires data to be processed on-the-fly with fast reaction …

Continuous Health Monitoring of Machinery using Online Clustering on Unlabeled Data Streams

2022 · 2022 IEEE International Conference on Big Data (Big Data)

Maintenance is an important support function to ensure the reliability, safety, and availability in the railway. Lately, machine learning has become a major player and allows practitioners to build intricate learning models for machinery maintenance. …

Choosing the Right Time to Learn Evolving Data Streams

2023

Continuous data generation over time presents new challenges for Machine Learning systems, which must develop real-time models due to memory and latency limitations. Streaming Machine Learning algorithms analyze data streams one sample at a time, …