3 papers
cs.LG2024
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…
cs.LG2024
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…
cs.LG2023
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…