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20192025
most citedEfficient Continual Learning in Neural Networks with Embedding Regularization

48 citations · 140 across the 16 of their papers we have counts for

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Showing 2024Show all

7 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,…

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.LG2024

How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies

Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski +4

Early exits enable the network's forward pass to terminate early by attaching trainable internal classifiers to the backbone network. Existing early-exit methods typically adopt ei…

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…

cs.LG2024★ 10 cited

Conditional computation in neural networks: principles and research trends

Simone Scardapane, Alessandro Baiocchi, Alessio Devoto +3

This article summarizes principles and ideas from the emerging area of applying \textit{conditional computation} methods to the design of neural networks. In particular, we focus o…

cs.LG2024★ 1 cited

Class incremental learning with probability dampening and cascaded gated classifier

Jary Pomponi, Alessio Devoto, Simone Scardapane

Humans are capable of acquiring new knowledge and transferring learned knowledge into different domains, incurring a small forgetting. The same ability, called Continual Learning,…

cs.LG2024★ 5 cited

NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks

Matteo Gambella, Jary Pomponi, Simone Scardapane +1

Early Exit Neural Networks (EENNs) endow astandard Deep Neural Network (DNN) with Early Exit Classifiers (EECs), to provide predictions at intermediate points of the processing whe…