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pro vyhledávání: '"Lombardi, Michele"'
The bin packing is a well-known NP-Hard problem in the domain of artificial intelligence, posing significant challenges in finding efficient solutions. Conversely, recent advancements in quantum technologies have shown promising potential for achievi
Externí odkaz:
http://arxiv.org/abs/2309.12678
Autor:
Silvestri, Mattia, Berden, Senne, Mandi, Jayanta, Mahmutoğulları, Ali İrfan, Amos, Brandon, Guns, Tias, Lombardi, Michele
Many real-world optimization problems contain parameters that are unknown before deployment time, either due to stochasticity or to lack of information (e.g., demand or travel times in delivery problems). A common strategy in such cases is to estimat
Externí odkaz:
http://arxiv.org/abs/2307.05213
Autor:
Marro, Samuele, Lombardi, Michele
Publikováno v:
40th International Conference on Machine Learning (ICML 2023)
In the context of adversarial robustness, we make three strongly related contributions. First, we prove that while attacking ReLU classifiers is $\mathit{NP}$-hard, ensuring their robustness at training time is $\Sigma^2_P$-hard (even on a single exa
Externí odkaz:
http://arxiv.org/abs/2306.14326
In the last decade, the scientific community has devolved its attention to the deployment of data-driven approaches in scientific research to provide accurate and reliable analysis of a plethora of phenomena. Most notably, Physics-informed Neural Net
Externí odkaz:
http://arxiv.org/abs/2306.10335
We make two contributions in the field of AI fairness over continuous protected attributes. First, we show that the Hirschfeld-Gebelein-Renyi (HGR) indicator (the only one currently available for such a case) is valuable but subject to a few crucial
Externí odkaz:
http://arxiv.org/abs/2305.18504
The interplay between Machine Learning (ML) and Constrained Optimization (CO) has recently been the subject of increasing interest, leading to a new and prolific research area covering (e.g.) Decision Focused Learning and Constrained Reinforcement Le
Externí odkaz:
http://arxiv.org/abs/2210.14030
Autor:
Teso, Stefano, Bliek, Laurens, Borghesi, Andrea, Lombardi, Michele, Yorke-Smith, Neil, Guns, Tias, Passerini, Andrea
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 variables are not known or are only partially specified. The challenge is to
Externí odkaz:
http://arxiv.org/abs/2205.10157
Publikováno v:
In Omega September 2024 127
Autor:
Lombardi, Michele <1980>
This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods ha
Externí odkaz:
http://amsdottorato.unibo.it/2961/
Publikováno v:
In Knowledge-Based Systems 4 November 2024 303