Leonardo Lucio Custode
@llcustode
Post doctoral researcher @ UniTN - ML, XAI
ID: 1211991189156614145
http://leocus.gitlab.io 31-12-2019 12:43:35
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Great news! 3 papers accepted at @IEEESSCI2021. Thanks to my coauthors Leonardo Lucio Custode and Anil Yaman!😎 #evolutionarycomputation #machinelearning #reinforcementlearning #neuralnetworks
Another step towards interpretable systems optimized through evolutionary computation made by Leonardo Lucio Custode and myself: arxiv.org/pdf/2202.04943… #Artificial_Intelligence #ai #explainability #explainableai #machinelearing #evolutionaryalgorithms
Interpretable AI for policy-making in pandemics deepai.org/publication/in… by Leonardo Lucio Custode and Giovanni Iacca #EvolutionaryComputation #ReinforcementLearning
This paper presents a method using #MachineLearning for automatic COVID-19 patient-stratification based on standardised lung #ultrasound data: doi.org/10.1121/2.0001… Leonardo Lucio Custode Giovanni Iacca Ultrasound Laboratory Trento #acoustics
Interested in Interpretable or Explainable Reinforcement Learning? In our latest published article, Giovanni Iacca and I present a method to perform Reinforcement Learning with Decision Trees, matching the state of the art in several benchmarks. Check it out: ieeexplore.ieee.org/document/10015…
I'm super-proud of Leonardo Lucio Custode! He is the first PhD graduate (cum laude!) in my group at Università di Trento UniTrento_DISI . Thanks Doina Jaume Bacardit and Libertario Demi (Ultrasound Laboratory Trento) for your participation to the defense and for the wonderful discussion. Ad maiora!
New paper out! sciencedirect.com/science/articl… We propose an evolutionary computation method for interpretable multi-agent reinforcement learning tasks. Leonardo Lucio Custode Andrea Ferigo and Marco Crespi. #XAI #MachineLearning
I am happy to share our recent paper on quality-diversity #optimization of #decisiontrees for #reinforcementlearning tasks. This approach can be useful to achieve #interpretability and #explainableai. #MachineLearning #xAI Andrea Ferigo Leonardo Lucio Custode doi.org/10.1007/s00521…
Our GECCO 2025 papers are finally out! Multi-Objective Evolutionary Hindsight Experience Replay for Robotics doi.org/10.1145/363852… Decentralized Federated NeuroEvolution of Heterogeneous Networks doi.org/10.1145/363852… Neuron-centric Hebbian Learning doi.org/10.1145/363852…
Happy to share that we won the Interpretable Control Competition @ #GECCO24 ! Congrats Mátyás Vincze Laura Ferrarotti Giovanni Iacca Bruno Lepri