collaborators

5 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

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…

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…

cs.LG2023

"It's a Match!" -- A Benchmark of Task Affinity Scores for Joint Learning

Raphael Azorin, Massimo Gallo, Alessandro Finamore +2

While the promises of Multi-Task Learning (MTL) are attractive, characterizing the conditions of its success is still an open problem in Deep Learning. Some tasks may benefit from…