18 citations · 79 across the 19 of their papers we have counts for
8 papers · 1 filter
Fine-grained Attention in Hierarchical Transformers for Tabular Time-series
Raphael Azorin, Zied Ben Houidi, Massimo Gallo +2
Tabular data is ubiquitous in many real-life systems. In particular, time-dependent tabular data, where rows are chronologically related, is typically used for recording historical…
Information Theoretic Text-to-Image Alignment
Chao Wang, Giulio Franzese, Alessandro Finamore +2
Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a labori…
Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
Data Augmentation (DA) -- enriching training data by adding synthetic samples -- is a technique widely adopted in Computer Vision (CV) and Natural Language Processing (NLP) tasks t…
Toward Generative Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
Data Augmentation (DA)-augmenting training data with synthetic samples-is wildly adopted in Computer Vision (CV) to improve models performance. Conversely, DA has not been yet popu…
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…
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification
Idio Guarino, Chao Wang, Alessandro Finamore +2
The popularity of Deep Learning (DL), coupled with network traffic visibility reduction due to the increased adoption of HTTPS, QUIC and DNS-SEC, re-ignited interest towards Traffi…