4 papers
A Unified Framework for Neural Computation and Learning Over Time
Stefano Melacci, Alessandro Betti, Michele Casoni +3
This paper proposes Hamiltonian Learning, a novel unified framework for learning with neural networks "over time", i.e., from a possibly infinite stream of data, in an online manne…
Continual Learning of Conjugated Visual Representations through Higher-order Motion Flows
Simone Marullo, Matteo Tiezzi, Marco Gori +1
Learning with neural networks from a continuous stream of visual information presents several challenges due to the non-i.i.d. nature of the data. However, it also offers novel opp…
Dynamic Decoupling of Placid Terminal Attractor-based Gradient Descent Algorithm
Jinwei Zhao, Marco Gori, Alessandro Betti +4
Gradient descent (GD) and stochastic gradient descent (SGD) have been widely used in a large number of application domains. Therefore, understanding the dynamics of GD and improvin…
Explainable Malware Detection with Tailored Logic Explained Networks
Peter Anthony, Francesco Giannini, Michelangelo Diligenti +4
Malware detection is a constant challenge in cybersecurity due to the rapid development of new attack techniques. Traditional signature-based approaches struggle to keep pace with…