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Found 5 papers, 1 papers with code
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments.
DiagNet: towards a generic, Internet-scale root cause analysis solution
Further, the set of possible problems and causes is not known in advance, making it impossible in practice to train a classifier with all combinations of problems, causes and locations.
Spores: Stateless Predictive Onion Routing for E-Squads
Mass surveillance of the population by state agencies and corporate parties is now a well-known fact.
Cluster-and-Conquer: When Randomness Meets Graph Locality
K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications.
Low-Cost Privacy-Aware Decentralized Learning
This paper introduces ZIP-DL, a novel privacy-aware decentralized learning (DL) algorithm that relies on adding correlated noise to each model update during the model training process.
