28 citations · 56 across the 5 of their papers we have counts for
13 papers
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens
Stefano Teso, Laurens Bliek, Andrea Borghesi +4
It is increasingly common to solve combinatorial optimisation problems that are partially-specified. We survey the case where the objective function or the relations between variab…
Deep Learning for Virus-Spreading Forecasting: a Brief Survey
Federico Baldo, Lorenzo Dall'Olio, Mattia Ceccarelli +5
The advent of the coronavirus pandemic has sparked the interest in predictive models capable of forecasting virus-spreading, especially for boosting and supporting decision-making…
A Machine Learning Approach to Online Fault Classification in HPC Systems
Alessio Netti, Zeynep Kiziltan, Ozalp Babaoglu +3
As High-Performance Computing (HPC) systems strive towards the exascale goal, failure rates both at the hardware and software levels will increase significantly. Thus, detecting an…
An Analysis of Regularized Approaches for Constrained Machine Learning
Michele Lombardi, Federico Baldo, Andrea Borghesi +1
Regularization-based approaches for injecting constraints in Machine Learning (ML) were introduced to improve a predictive model via expert knowledge. We tackle the issue of findin…
Improving Deep Learning Models via Constraint-Based Domain Knowledge: a Brief Survey
Andrea Borghesi, Federico Baldo, Michela Milano
Deep Learning (DL) models proved themselves to perform extremely well on a wide variety of learning tasks, as they can learn useful patterns from large data sets. However, purely d…
Combining Learning and Optimization for Transprecision Computing
Andrea Borghesi, Giuseppe Tagliavini, Michele Lombardi +2
The growing demands of the worldwide IT infrastructure stress the need for reduced power consumption, which is addressed in so-called transprecision computing by improving energy e…