3 papers
cs.LG2026
Quantization-Aware Regularizers for Deep Neural Networks Compression
Dario Malchiodi, Mattia Ferraretto, Marco Frasca
Deep Neural Networks reached state-of-the-art performance across numerous domains, but this progress has come at the cost of increasingly large and over-parameterized models, posin…
cs.LG2024
Support Vector Based Anomaly Detection in Federated Learning
Massimo Frasson, Dario Malchiodi
Anomaly detection plays a crucial role in various domains, from cybersecurity to industrial systems. However, traditional centralized approaches often encounter challenges related…
cs.LG2021
On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters
Giacomo Fumagalli, Davide Raimondi, Raffaele Giancarlo +2
Bloom Filters are a fundamental and pervasive data structure. Within the growing area of Learned Data Structures, several Learned versions of Bloom Filters have been considered, yi…