Luca Franceschi

According to our database, Luca Franceschi authored at least 26 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hyperparameter Optimization in Machine Learning.

Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi

CoRR, 2024

Jet Expansions of Residual Computation.

Yihong Chen, Xiangxiang Xu, Yao Lu, Pontus Stenetorp, Luca Franceschi

CoRR, 2024

Evaluating Large Language Models with fmeval.

Pola Schwöbel, Luca Franceschi, Muhammad Bilal Zafar, Keerthan Vasist, Aman Malhotra, Tomer Shenhar, Pinal Tailor, Pinar Yilmaz, Michael Diamond, Michele Donini

CoRR, 2024

Explaining Probabilistic Models with Distributional Values.

Luca Franceschi, Michele Donini, Cédric Archambeau, Matthias W. Seeger

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography.

Luca Franceschi, Cemre Zor, Muhammad Bilal Zafar, Gianluca Detommaso, Cédric Archambeau, Tamas Madl, Michele Donini, Matthias W. Seeger

Proceedings of the Trustworthy Machine Learning for Healthcare, 2023

Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls".

Mia C. Mayer, Muhammad Bilal Zafar, Luca Franceschi, Huzefa Rangwala

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

DAG Learning on the Permutahedron.

Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models.

Pasquale Minervini, Luca Franceschi, Mathias Niepert

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning Discrete Directed Acyclic Graphs via Backpropagation.

Andrew J. Wren, Pasquale Minervini, Luca Franceschi, Valentina Zantedeschi

CoRR, 2022

ReFactorGNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.

Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel

CoRR, 2022

ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.

Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

A unified framework for gradient-based hyperparameter optimization and meta-learning.

Luca Franceschi

PhD thesis, 2021

Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions.

Mathias Niepert, Pasquale Minervini, Luca Franceschi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Marthe: Scheduling the Learning Rate Via Online Hypergradients.

Michele Donini, Luca Franceschi, Orchid Majumder, Massimiliano Pontil, Paolo Frasconi

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

On the Iteration Complexity of Hypergradient Computation.

Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Fast and Continuous Foothold Adaptation for Dynamic Locomotion Through CNNs.

Octavio Antonio Villarreal-Magaña, Victor Barasuol, Marco Camurri, Luca Franceschi, Michele Focchi, Massimiliano Pontil, Darwin G. Caldwell, Claudio Semini

IEEE Robotics Autom. Lett., 2019

Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm.

Michele Donini, Luca Franceschi, Massimiliano Pontil, Orchid Majumder, Paolo Frasconi

CoRR, 2019

Learning Discrete Structures for Graph Neural Networks.

Luca Franceschi, Mathias Niepert, Massimiliano Pontil, Xiao He

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Fast and Continuous Foothold Adaptation for Dynamic Locomotion through Convolutional Neural Networks.

Octavio Antonio Villarreal-Magaña, Victor Barasuol, Marco Camurri, Michele Focchi, Luca Franceschi, Massimiliano Pontil, Darwin G. Caldwell, Claudio Semini

CoRR, 2018

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning.

Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, Paolo Frasconi

CoRR, 2018

Bilevel Programming for Hyperparameter Optimization and Meta-Learning.

Luca Franceschi, Paolo Frasconi, Saverio Salzo, Massimiliano Pontil

CoRR, 2018

Bilevel Programming for Hyperparameter Optimization and Meta-Learning.

Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, Massimiliano Pontil

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

A Bridge Between Hyperparameter Optimization and Larning-to-learn.

Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil

CoRR, 2017

A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion.

Leonardo Badino, Luca Franceschi, Raman Arora, Michele Donini, Massimiliano Pontil

Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017

Forward and Reverse Gradient-Based Hyperparameter Optimization.

Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil

Proceedings of the 34th International Conference on Machine Learning, 2017

On Hyperparameter Optimization in Learning Systems.

Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil

Proceedings of the 5th International Conference on Learning Representations, 2017