51 citations · 300 across the 23 of their papers we have counts for
7 papers · 1 filter
Incremental Learning with Concept Drift Detection and Prototype-based Embeddings for Graph Stream Classification
Kleanthis Malialis, Jin Li, Christos G. Panayiotou +1
Data stream mining aims at extracting meaningful knowledge from continually evolving data streams, addressing the challenges posed by nonstationary environments, particularly, conc…
Unsupervised Unlearning of Concept Drift with Autoencoders
André Artelt, Kleanthis Malialis, Christos Panayiotou +2
Concept drift refers to a change in the data distribution affecting the data stream of future samples. Consequently, learning models operating on the data stream might become obsol…
Data augmentation on-the-fly and active learning in data stream classification
Kleanthis Malialis, Dimitris Papatheodoulou, Stylianos Filippou +2
There is an emerging need for predictive models to be trained on-the-fly, since in numerous machine learning applications data are arriving in an online fashion. A critical challen…
A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification
Kleanthis Malialis, Manuel Roveri, Cesare Alippi +2
In real-world applications, the process generating the data might suffer from nonstationary effects (e.g., due to seasonality, faults affecting sensors or actuators, and changes in…
Nonstationary data stream classification with online active learning and siamese neural networks
Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou
We have witnessed in recent years an ever-growing volume of information becoming available in a streaming manner in various application areas. As a result, there is an emerging nee…
Data-efficient Online Classification with Siamese Networks and Active Learning
Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou
An ever increasing volume of data is nowadays becoming available in a streaming manner in many application areas, such as, in critical infrastructure systems, finance and banking,…
Online Learning With Adaptive Rebalancing in Nonstationary Environments
Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou
An enormous and ever-growing volume of data is nowadays becoming available in a sequential fashion in various real-world applications. Learning in nonstationary environments consti…