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ORCIDLeonardo Lucio Custode
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2020 – today
- 2024
[c19]Elia Cunegatti
, Leonardo Lucio Custode, Giovanni Iacca:
Many-Objective Evolutionary Influence Maximization: Balancing Spread, Budget, Fairness, and Time. GECCO Companion 2024: 655-658- [c18]Leonardo Lucio Custode, Fabio Caraffini, Anil Yaman, Giovanni Iacca:
An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms. GECCO Companion 2024: 1838-1845 - [c17]Leonardo Lucio Custode, Ivanoe De Falco, Antonio Della Cioppa, Giovanni Iacca, Umberto Scafuri:
NEvoFed: A Decentralized Approach to Federated NeuroEvolution of Heterogeneous Neural Networks. GECCO 2024 - [c16]Leonardo Lucio Custode, Chiara Camilla Rambaldi Migliore, Marco Roveri, Giovanni Iacca:
Comparing Large Language Models and Grammatical Evolution for Code Generation. GECCO Companion 2024: 1830-1837 - [c15]Leonardo Lucio Custode, Pietro Farina, Eren Yildiz, Renan Beran Kilic, Kasim Sinan Yildirim, Giovanni Iacca:
Fast-Inf: Ultra-Fast Embedded Intelligence on the Batteryless Edge. SenSys 2024: 239-252 - [i12]Leonardo Lucio Custode, Giovanni Iacca:
Social Interpretable Reinforcement Learning. CoRR abs/2401.15480 (2024) - [i11]Elia Cunegatti, Leonardo Lucio Custode, Giovanni Iacca:
Many-Objective Evolutionary Influence Maximization: Balancing Spread, Budget, Fairness, and Time. CoRR abs/2403.18755 (2024) - [i10]Leonardo Lucio Custode, Fabio Caraffini, Anil Yaman, Giovanni Iacca:
An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms. CoRR abs/2408.02451 (2024) - [i9]Elia Cunegatti, Leonardo Lucio Custode, Giovanni Iacca:
Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training. CoRR abs/2411.07066 (2024) - [i8]Mátyás Vincze, Laura Ferrarotti, Leonardo Lucio Custode, Bruno Lepri, Giovanni Iacca:
SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks. CoRR abs/2412.13053 (2024) - 2023
- [j6]Leonardo Lucio Custode, Giovanni Iacca:
Evolutionary Learning of Interpretable Decision Trees. IEEE Access 11: 6169-6184 (2023) - [j5]Leonardo Lucio Custode, Federico Mento, Francesco Tursi, Andrea Smargiassi, Riccardo Inchingolo, Tiziano Perrone, Libertario Demi, Giovanni Iacca:
Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees. Appl. Soft Comput. 133: 109926 (2023) - [j4]Marco Crespi, Andrea Ferigo, Leonardo Lucio Custode, Giovanni Iacca:
A population-based approach for multi-agent interpretable reinforcement learning. Appl. Soft Comput. 147: 110758 (2023) - [c14]Mir Hassan, Leonardo Lucio Custode, Kasim Sinan Yildirim, Giovanni Iacca:
FedEdge: Federated Learning with Docker and Kubernetes forScalable and Efficient Edge Computing. EWSN 2023: 339-344 - [c13]Andrea Ferigo, Leonardo Lucio Custode, Giovanni Iacca:
Quality Diversity Evolutionary Learning of Decision Trees. SAC 2023: 425-432 - 2022
- [j3]Leonardo Lucio Custode, Hyunho Mo, Andrea Ferigo, Giovanni Iacca:
Evolutionary Optimization of Spiking Neural P Systems for Remaining Useful Life Prediction. Algorithms 15(3): 98 (2022) - [c12]Alberto Carbognin, Leonardo Lucio Custode, Giovanni Iacca:
Genetic Improvement of TCP Congestion Avoidance. BIOMA 2022: 114-126 - [c11]Marco Crespi, Leonardo Lucio Custode, Giovanni Iacca:
Towards Interpretable Policies in Multi-agent Reinforcement Learning Tasks. BIOMA 2022: 262-276 - [c10]Leonardo Lucio Custode, Hyunho Mo, Giovanni Iacca:
Neuroevolution of Spiking Neural P Systems. EvoApplications 2022: 435-451 - [c9]Leonardo Lucio Custode, Giovanni Iacca:
Interpretable pipelines with evolutionary optimized modules for reinforcement learning tasks with visual inputs. GECCO Companion 2022: 224-227 - [c8]Leonardo Lucio Custode, Giovanni Iacca:
Interpretable AI for policy-making in pandemics. GECCO Companion 2022: 1763-1769 - [c7]Gary White, Leonardo Lucio Custode, Owen O'Brien:
SASH: Safe Autonomous Self-Healing. ICSOC Workshops 2022: 142-153 - [i7]Leonardo Lucio Custode, Giovanni Iacca:
Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs. CoRR abs/2202.04943 (2022) - [i6]Leonardo Lucio Custode, Giovanni Iacca:
Interpretable AI for policy-making in pandemics. CoRR abs/2204.04256 (2022) - [i5]Andrea Ferigo, Leonardo Lucio Custode, Giovanni Iacca:
Quality Diversity Evolutionary Learning of Decision Trees. CoRR abs/2208.12758 (2022) - 2021
- [j2]Hyunho Mo, Leonardo Lucio Custode, Giovanni Iacca:
Evolutionary neural architecture search for remaining useful life prediction. Appl. Soft Comput. 108: 107474 (2021) - [j1]Michela Lorandi, Leonardo Lucio Custode, Giovanni Iacca:
Genetic Improvement of Routing Protocols for Delay Tolerant Networks. ACM Trans. Evol. Learn. Optim. 1(1): 4:1-4:37 (2021) - [c6]Michela Lorandi, Leonardo Lucio Custode, Giovanni Iacca:
Genetic improvement of routing in delay tolerant networks. GECCO Companion 2021: 35-36 - [c5]Quintino Francesco Lotito, Leonardo Lucio Custode, Giovanni Iacca:
A signal-centric perspective on the evolution of symbolic communication. GECCO 2021: 120-128 - [c4]Hao Qiu, Leonardo Lucio Custode, Giovanni Iacca:
Black-box adversarial attacks using evolution strategies. GECCO Companion 2021: 1827-1833 - [c3]Leonardo Lucio Custode, Giovanni Iacca:
One run to attack them all: finding simultaneously multiple targeted adversarial perturbations. SSCI 2021: 1-8 - [c2]Leonardo Lucio Custode, Giovanni Iacca:
A co-evolutionary approach to interpretable reinforcement learning in environments with continuous action spaces. SSCI 2021: 1-8 - [i4]Michela Lorandi, Leonardo Lucio Custode, Giovanni Iacca:
Genetic Improvement of Routing Protocols for Delay Tolerant Networks. CoRR abs/2103.07428 (2021) - [i3]Quintino Francesco Lotito, Leonardo Lucio Custode, Giovanni Iacca:
A Signal-Centric Perspective on the Evolution of Symbolic Communication. CoRR abs/2103.16882 (2021) - [i2]Hao Qiu, Leonardo Lucio Custode, Giovanni Iacca:
Black-box adversarial attacks using Evolution Strategies. CoRR abs/2104.15064 (2021) - 2020
- [c1]Leonardo Lucio Custode, Ciro Lucio Tecce, Illya Bakurov, Mauro Castelli, Antonio Della Cioppa, Leonardo Vanneschi:
A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks. EvoApplications 2020: 513-529 - [i1]Leonardo Lucio Custode, Giovanni Iacca:
Evolutionary learning of interpretable decision trees. CoRR abs/2012.07723 (2020)
Coauthor Index
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