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5 papers · 1 filter
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation
Alessandro Finamore, Chao Wang, Jonatan Krolikowski +3
Over the last years we witnessed a renewed interest toward Traffic Classification (TC) captivated by the rise of Deep Learning (DL). Yet, the vast majority of TC literature lacks c…
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias
Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko
Self-training is a well-known approach for semi-supervised learning. It consists of iteratively assigning pseudo-labels to unlabeled data for which the model is confident and treat…
LogPrécis: Unleashing Language Models for Automated Malicious Log Analysis
Matteo Boffa, Rodolfo Vieira Valentim, Luca Vassio +4
The collection of security-related logs holds the key to understanding attack behaviors and diagnosing vulnerabilities. Still, their analysis remains a daunting challenge. Recently…
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
Yijun Wan, Melih Barsbey, Abdellatif Zaidi +1
Neural network compression has been an increasingly important subject, not only due to its practical relevance, but also due to its theoretical implications, as there is an explici…
Energy Efficient Operation of Adaptive Massive MIMO 5G HetNets
Siddarth Marwaha, Eduard A. Jorswieck, Mostafa Jassim +4
For energy efficient operation of the massive multiple-input multiple-output (MIMO) networks, various aspects of energy efficiency maximization have been addressed, where a careful…