76 citations
11 papers
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…
Survey on Machine Learning for Traffic-Driven Service Provisioning in Optical Networks
Tania Panayiotou, Maria Michalopoulou, Georgios Ellinas
The unprecedented growth of the global Internet traffic, coupled with the large spatio-temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are…
Modeling Soft-Failure Evolution for Triggering Timely Repair with Low QoT Margins
Sadananda Behera, Tania Panayiotou, Georgios Ellinas
In this work, the capabilities of an encoder-decoder learning framework are leveraged to predict soft-failure evolution over a long future horizon. This enables the triggering of t…
SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities
Koorosh Aslansefat, Panagiota Nikolaou, Martin Walker +9
The use of Unmanned Arial Vehicles (UAVs) offers many advantages across a variety of applications. However, safety assurance is a key barrier to widespread usage, especially given…
Periodic and Event-Triggering for Joint Capacity Maximization and Safe Intersection Crossing
Christian Vitale, Panayiotis Kolios, Georgios Ellinas
Intersection crossing represents a bottleneck for transportation systems and Connected Autonomous Vehicles (CAVs) may be the groundbreaking solution to the problem. This work propo…