activity
20202022
most citedA First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification

14 citations · 28 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI20222 cited

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…

cs.LG20213 cited

Thinkback: Task-SpecificOut-of-Distribution Detection

Lixuan Yang, Dario Rossi

The increased success of Deep Learning (DL) has recently sparked large-scale deployment of DL models in many diverse industry segments. Yet, a crucial weakness of supervised model…

cs.NI202114 cited

A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification

Giampaolo Bovenzi, Lixuan Yang, Alessandro Finamore +4

The recent popularity growth of Deep Learning (DL) re-ignited the interest towards traffic classification, with several studies demonstrating the accuracy of DL-based classifiers t…

cs.LG2021

Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications

Lixuan Yang, Alessandro Finamore, Feng Jun +1

The increasing success of Machine Learning (ML) and Deep Learning (DL) has recently re-sparked interest towards traffic classification. While classification of known traffic is a w…

cs.LG20209 cited

Heterogeneous Data-Aware Federated Learning

Lixuan Yang, Cedric Beliard, Dario Rossi

Federated learning (FL) is an appealing concept to perform distributed training of Neural Networks (NN) while keeping data private. With the industrialization of the FL framework,…