109 citations · 227 across the 12 of their papers we have counts for
12 papers
The IJCNN 2025 Review Process
Michele Scarpiniti, Danilo Comminiello
The International Joint Conference on Neural Networks (IJCNN) is the premier international conference in the area of neural networks theory, analysis, and applications. The 2025 ed…
AFAFed -- Protocol analysis
Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh +1
In this paper, we design, analyze the convergence properties and address the implementation aspects of AFAFed. This is a novel Asynchronous Fair Adaptive Federated learning framewo…
Gomoku: analysis of the game and of the player Wine
Lorenzo Piazzo, Michele Scarpiniti, Enzo Baccarelli
Gomoku, also known as five in a row, is a classical board game, ideally suited for quickly testing novel Artificial Intelligence (AI) techniques. With the aim of facilitating a dev…
A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling
Danilo Comminiello, Alireza Nezamdoust, Simone Scardapane +3
Nonlinear models are known to provide excellent performance in real-world applications that often operate in non-ideal conditions. However, such applications often require online p…
Combined Sparse Regularization for Nonlinear Adaptive Filters
Danilo Comminiello, Michele Scarpiniti, Simone Scardapane +2
Nonlinear adaptive filters often show some sparse behavior due to the fact that not all the coefficients are equally useful for the modeling of any nonlinearity. Recently, a class…
Why should we add early exits to neural networks?
Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli +1
Deep neural networks are generally designed as a stack of differentiable layers, in which a prediction is obtained only after running the full stack. Recently, some contributions h…
A Multimodal Deep Network for the Reconstruction of T2W MR Images
Antonio Falvo, Danilo Comminiello, Simone Scardapane +2
Multiple sclerosis is one of the most common chronic neurological diseases affecting the central nervous system. Lesions produced by the MS can be observed through two modalities o…
Efficient data augmentation using graph imputation neural networks
Indro Spinelli, Simone Scardapane, Michele Scarpiniti +1
Recently, data augmentation in the semi-supervised regime, where unlabeled data vastly outnumbers labeled data, has received a considerable attention. In this paper, we describe an…
EcoMobiFog -- Design and Dynamic Optimization of a 5G Mobile-Fog-Cloud Multi-Tier Ecosystem for the Real-Time Distributed Execution of Stream Applications
Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh
The emerging 5G paradigm will enable multi-radio smartphones to run high-rate stream applications. However, since current smartphones remain resource and battery-limited, the 5G er…
Fog-supported delay-constrained energy-saving live migration of VMs over MultiPath TCP/IP 5G connections
Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh
The incoming era of the Fifth-Generation Fog Computing-supported Radio Access Networks (shortly, 5G FOGRANs) aims at exploiting computing/networking resource virtualization, in ord…
Learning activation functions from data using cubic spline interpolation
Simone Scardapane, Michele Scarpiniti, Danilo Comminiello +1
Neural networks require a careful design in order to perform properly on a given task. In particular, selecting a good activation function (possibly in a data-dependent fashion) is…
Perturbations of superstable linear hyperbolic systems
I. Kmit, N. Lyul'ko
The paper deals with initial-boundary value problems for linear non-autonomous first order hyperbolic systems whose solutions stabilize to zero in a finite time. We prove that prob…