Publications (4)
On the Convergence of Stochastic Gradient Descent in Low-precision Number Formats
Matteo Cacciola, Antonio Frangioni, Masoud Asgharian +2
Deep learning models are dominating almost all artificial intelligence tasks such as vision, text, and speech processing. Stochastic Gradient Descent (SGD) is the main tool for tra…
Deep Neural Networks pruning via the Structured Perspective Regularization
Matteo Cacciola, Antonio Frangioni, Xinlin Li +1
In Machine Learning, Artificial Neural Networks (ANNs) are a very powerful tool, broadly used in many applications. Often, the selected (deep) architectures include many layers, an…
Structured Pruning of Neural Networks for Constraints Learning
Matteo Cacciola, Antonio Frangioni, Andrea Lodi
In recent years, the integration of Machine Learning (ML) models with Operation Research (OR) tools has gained popularity across diverse applications, including cancer treatment, a…
The Differentiable Feasibility Pump
Matteo Cacciola, Alexandre Forel, Antonio Frangioni +1
Although nearly 20 years have passed since its conception, the feasibility pump algorithm remains a widely used heuristic to find feasible primal solutions to mixed-integer linear…