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LCSL

The Laboratory for Computational and Statistical Learning (LCSL) is one of the research units within MaLGa, the machine learning center of the University of Genova. LCSL focuses on the development of efficient and reliable machine learning algorithms blending tools from statistics, optimization, and regularization theory.

Our goal is to develop theoretically grounded and practical machine learning algorithms. In collaboration with other MaLGa units and external collaborators we work on foundational aspects of Machine Learning (CHARML) and also a number of applications including vision (MLV), robotics, and biological behavior (PiMLB).

People

  • Annalisa
    Barla

  • Simone
    Di Marino

  • Cesare
    Molinari

  • Lorenzo
    Rosasco

  • Silvia
    Villa

  • Cheik
    Traoré

  • Francesco
    Montagna

  • Edoardo
    Caldarelli

  • Emilia
    Magnani

  • Arnaud
    Watusadisi

  • Ilaria
    Stanzani

  • Marco
    Letizia

  • Andrea
    Della Vec…

  • Hippolyte
    Labarrière

  • Shuo
    Huang

  • Emanuele
    Naldi

  • Pietro
    Zerbetto

  • Stefano
    Ravera

  • Elena
    Milano

  • Rayan
    Autones

  • Joachim
    Bona-Pellis…

Past People

People
  • Ettore Fincato | 2023 → 2024 | PhD student

  • Marco Rando | 2020 → 2024 | PhD student

  • Cristian Jesus Vega Cereno | 2021 → 2024 | PhD student | Optimization

  • Jonathan Chirinos Rodriguez | 2024 | PhD student

  • Antoine Chatalic | 2021 → 2024 | Post-doctoral fellow

  • Rosanna Turrisi | 2023 → 2024 | Post-doctoral fellow | Machine Learning

  • Elisa Maiettini | 2021 → 2023 | Post-doctoral fellow

  • Nicolas Schreuder | 2020 → 2023 | Post-doctoral fellow

  • Vassilis Apidopoulos | 2019 → 2023 | Post-doctoral fellow

  • Gabriele Bortolai | 2023 | Student

  • Andrea Maracani | 2020 → 2023 | PhD student

  • Federico Ceola | 2020 → 2023 | PhD student

  • Ilaria Stanzani | 2023 | Research Scholar | Machine Learning

  • Andrea Della Vecchia | 2022 → 2023 | Research Scholar | Machine Learning

  • Paolo Didier Alfano | 2022 → 2023 | Research Scholar | Machine Learning and vision

  • Silvia Vertemati | 2023 | Student

  • Daniele Giampaoli | 2022 | Student | Structured Learning

  • Sophie Langer | 2022 | Post-doctoral fellow

  • Giulia Denevi | 2021 → 2022 | Post-doctoral fellow

  • Raffaello Camoriano | 2018 → 2022 | Post-doctoral fellow

  • Alexandra Gronholz | 2021 → 2022 | Post-doctoral fellow | Machine Learning

  • Andrea Della Vecchia | 2019 → 2022 | PhD student | Machine Learning

  • Denise D'Auria | 2022 | Student | Bioinformatics

  • Paolo Didier Alfano | 2019 → 2022 | PhD student | Machine Learning and vision

  • Stefano Vigogna | 2020 → 2022 | Post-doctoral fellow

  • Sara Frusone | 2022 | Student |

  • Nicolò Pagliana | 2019 → 2022 | PhD student | Machine Learning

  • Mathurin Massias | 2020 → 2022 | Post-doctoral fellow

  • Davide Garbarino | 2018 → 2021 | PhD student | Machine Learning

  • David Kozak | 2021 | PhD student

  • Rodolfo Assereto | 2021 | Student | Machine Learning

  • Simone Grossi | 2020 → 2021 | Research Scholar | Data driven web redesign

  • Sofiane Tanji | 2021 | Student

  • Maximilian Nickel | 2020 | Post-doctoral fellow

  • Carlo Ciliberto | 2019 → 2020 | Post-doctoral fellow

  • Guillaume Garrigos | 2019 → 2020 | Post-doctoral fellow

  • Enrico Cecini | 2020 | PhD student | Machine Learning

  • Junhong Lin | 2019 → 2020 | Post-doctoral fellow

  • Jaouad Mourtada | 2020 | Post-doctoral fellow

  • Nicole Mucke | 2020 | Post-doctoral fellow

  • Gian Maria Marconi | 2020 | PhD student | Machine Learning

  • Nicolò Ginatta | 2019 → 2020 | PhD student | Machine Learning

  • Dominic Richards | 2020 | PhD student

  • Veronica Tozzo | 2020 | Research Scholar | Machine Learning

  • Riccardo Bianchini | 2020 | Student | Machine Learning

  • Luigi Carratino | 2017 → 2020 | Post-doctoral fellow

  • Daniele Calandriello | 2018 → 2019 | Post-doctoral fellow

  • Fabio Anselmi | 2017 → 2019 | Post-doctoral fellow | Machine Learning |

  • Vincenzo Petito | 2019 | Student | Machine Learning

  • Amartya Sanyal | 2019 | Student

  • Manuel Orlandi | 2018 | Student | Machine Learning

  • Lorenzo Spano | 2018 | Student | Machine Learning

  • Luca Biggio | 2018 | Student | Machine Learning

  • Michele Dall’Oro | 2017 | Student | Machine Learning

  • Luca Demetrio | 2017 | Student | Machine Learning

  • Alessandro Rudi | 2014 → 2016 | Post-doctoral fellow

  • Alessio Russo | 2016 | Student | Machine Learning

  • Daniele Surpano | 2016 | Student | Machine Learning

  • Soahib Ali Syed | 2013 → 2016 | PhD student | Machine Learning

  • Gianluca Salvaia | 2016 | Student | Machine Learning

  • Luigi Carratino | 2016 | Student | Machine Learning

  • Alessandro Rudi | 2014 | PhD student | Machine Learning

  • Nicola Rebagliati | 2009 | Student | Machine Learning

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    Research projects

    Most recent LCSL research projects

    Publications

    Most recent LCSL publications

    TitleYearAuthorVenue
    NLP-based tools for localization of the epileptogenic zone in patients with drug-resistant focal epilepsy2024Mora Sara; Turrisi Rosanna; Chiarella Lorenzo; Consales Alessandro; Tassi Laura; Mai Roberto; Nobili Lino; Barla Annalisa; Arnulfo GabrieleSCIENTIFIC REPORTS
    RESPRECT: Speeding-up Multi-Fingered Grasping With Residual Reinforcement Learning2024Ceola Federico; Rosasco Lorenzo; Natale LorenzoIEEE ROBOTICS AND AUTOMATION LETTERS
    Iterative regularization for low complexity regularizers2024Molinari C.; Massias M.; Rosasco L.; Villa S.NUMERISCHE MATHEMATIK
    Assumption violations in causal discovery and the robustness of score matching2024Montagna Francesco; Mastakouri Atalanti A.; Eulig Elias; Noceti Nicoletta; Rosasco Lorenzo; Janzing Dominik; Aragam Bryon; Locatello FrancescoAdvances in Neural Information Processing Systems
    Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods2024Alfano P. D.; Pastore V. P.; Rosasco L.; Odone F.IMAGE AND VISION COMPUTING