1 citations · 2 across the 3 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.NI2026
Beyond Measurement Metrics: A Human-Centered Framework for Semantic Validation of Network Traffic Classification
Igor Cherepanov, David Sessler, Alex Ulmer +2
Machine learning (ML) has become the dominant approach for network traffic classification, achieving very high predictive performance. However, a model is only valuable if it learn…
cs.HC2026
Interactive Analysis of Global Explanations using Aggregated Class Activation Maps for Network Data
Igor Cherepanov, David Sessler, Alex Ulmer +3
Recent machine learning (ML) advances have demonstrated that deep learning (DL) achieves impressive results in different application domains, including the classification of comput…