1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Resource-Limited Automated Ki67 Index Estimation in Breast Cancer
J. Gliozzo, G. Marinò, A. Bonometti +2
The prediction of tumor progression and chemotherapy response has been recently tackled exploiting Tumor Infiltrating Lymphocytes (TILs) and the nuclear protein Ki67 as prognostic…
A Critical Analysis of Classifier Selection in Learned Bloom Filters
Dario Malchiodi, Davide Raimondi, Giacomo Fumagalli +2
Learned Bloom Filters, i.e., models induced from data via machine learning techniques and solving the approximate set membership problem, have recently been introduced with the aim…
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…