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20172026
most citedGraph topology inference based on sparsifying transform learning

73 citations · 139 across the 34 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.LG2024

Goal-oriented Communications based on Recursive Early Exit Neural Networks

Jary Pomponi, Mattia Merluzzi, Alessio Devoto +3

This paper presents a novel framework for goal-oriented semantic communications leveraging recursive early exit models. The proposed approach is built on two key components. First,…

eess.SP2024

Topological Signal Processing and Learning: Recent Advances and Future Challenges

Elvin Isufi, Geert Leus, Baltasar Beferull-Lozano +2

Developing methods to process irregularly structured data is crucial in applications like gene-regulatory, brain, power, and socioeconomic networks. Graphs have been the go-to alge…

cs.CV2024★ 1 cited

Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning

Alessio Devoto, Federico Alvetreti, Jary Pomponi +3

Recently, foundation models based on Vision Transformers (ViTs) have become widely available. However, their fine-tuning process is highly resource-intensive, and it hinders their…

cs.IT2024

Adaptive Semantic Token Selection for AI-native Goal-oriented Communications

Alessio Devoto, Simone Petruzzi, Jary Pomponi +2

In this paper, we propose a novel design for AI-native goal-oriented communications, exploiting transformer neural networks under dynamic inference constraints on bandwidth and com…

eess.SP2024★ 1 cited

Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach

Emilio Calvanese Strinati, Paolo Di Lorenzo, Vincenzo Sciancalepore +17

Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requir…