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UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning


Oct 25, 2022
Mattia Silvestri, Allegra De Filippo, Michele Lombardi, Michela Milano

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Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens


May 20, 2022
Stefano Teso, Laurens Bliek, Andrea Borghesi, Michele Lombardi, Neil Yorke-Smith, Tias Guns, Andrea Passerini

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Deep Learning for Virus-Spreading Forecasting: a Brief Survey


Mar 03, 2021
Federico Baldo, Lorenzo Dall'Olio, Mattia Ceccarelli, Riccardo Scheda, Michele Lombardi, Andrea Borghesi, Stefano Diciotti, Michela Milano

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Discrete solution pools and noise-contrastive estimation for predict-and-optimize


Nov 10, 2020
Maxime Mulamba, Jayanta Mandi, Michelangelo Diligenti, Michele Lombardi, Victor Bucarey, Tias Guns

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An Analysis of Regularized Approaches for Constrained Machine Learning


May 20, 2020
Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano

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Teaching the Old Dog New Tricks: Supervised Learning with Constraints


Feb 25, 2020
Fabrizio Detassis, Michele Lombardi, Michela Milano

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Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem


Feb 25, 2020
Mattia Silvestri, Michele Lombardi, Michela Milano

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Injective Domain Knowledge in Neural Networks for Transprecision Computing


Feb 24, 2020
Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano

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A Lagrangian Dual Framework for Deep Neural Networks with Constraints


Jan 26, 2020
Ferdinando Fioretto, Terrence WK Mak, Federico Baldo, Michele Lombardi, Pascal Van Hentenryck

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Anomaly Detection using Autoencoders in High Performance Computing Systems


Nov 13, 2018
Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini

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* 9 pages, 3 figures 

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