14 citations · 33 across the 9 of their papers we have counts for
10 papers
Cross-network transferable neural models for WLAN interference estimation
Danilo Marinho Fernandes, Jonatan Krolikowski, Zied Ben Houidi +2
Airtime interference is a key performance indicator for WLANs, measuring, for a given time period, the percentage of time during which a node is forced to wait for other transmissi…
Rare Yet Popular: Evidence and Implications from Labeled Datasets for Network Anomaly Detection
Jose Manuel Navarro, Alexis Huet, Dario Rossi
Anomaly detection research works generally propose algorithms or end-to-end systems that are designed to automatically discover outliers in a dataset or a stream. While literature…
Quality Monitoring and Assessment of Deployed Deep Learning Models for Network AIOps
Lixuan Yang, Dario Rossi
Artificial Intelligence (AI) has recently attracted a lot of attention, transitioning from research labs to a wide range of successful deployments in many fields, which is particul…
Neural combinatorial optimization beyond the TSP: Existing architectures under-represent graph structure
Matteo Boffa, Zied Ben Houidi, Jonatan Krolikowski +1
Recent years have witnessed the promise that reinforcement learning, coupled with Graph Neural Network (GNN) architectures, could learn to solve hard combinatorial optimization pro…
Human readable network troubleshooting based on anomaly detection and feature scoring
Jose M. Navarro, Alexis Huet, Dario Rossi
Network troubleshooting is still a heavily human-intensive process. To reduce the time spent by human operators in the diagnosis process, we present a system based on (i) unsupervi…
HURRA! Human readable router anomaly detection
Jose M. Navarro, Dario Rossi
This paper presents HURRA, a system that aims to reduce the time spent by human operators in the process of network troubleshooting. To do so, it comprises two modules that are plu…