On Hyperparameter Optimization in Learning Systems. - Luca Franceschi 001; Michele Donini; Paolo Frasconi; Massimiliano Pontil (ICLR (Workshop), 2017)

Forward and Reverse Gradient-Based Hyperparameter Optimization. - Luca Franceschi 001; Michele Donini; Paolo Frasconi; Massimiliano Pontil (ICML, 2017)

A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion. - Leonardo Badino; Luca Franceschi 001; Raman Arora; Michele Donini; Massimiliano Pontil (INTERSPEECH, 2017)

A Bridge Between Hyperparameter Optimization and Larning-to-learn. - Luca Franceschi 001; Michele Donini; Paolo Frasconi; Massimiliano Pontil (CoRR, 2017)

Bilevel Programming for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Paolo Frasconi; Saverio Salzo; Riccardo Grazzi; Massimiliano Pontil (ICML, 2018)

Bilevel Programming for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Paolo Frasconi; Saverio Salzo; Massimiliano Pontil (CoRR, 2018)

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Riccardo Grazzi; Massimiliano Pontil; Saverio Salzo; Paolo Frasconi (CoRR, 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 001; Massimiliano Pontil; Darwin G. Caldwell; Claudio Semini (CoRR, 2018)

Learning Discrete Structures for Graph Neural Networks. - Luca Franceschi 001; Mathias Niepert; Massimiliano Pontil; Xiao He (ICML, 2019)

Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm. - Michele Donini; Luca Franceschi 001; Massimiliano Pontil; Orchid Majumder; Paolo Frasconi (CoRR, 2019)

Fast and Continuous Foothold Adaptation for Dynamic Locomotion Through CNNs. - Octavio Antonio Villarreal-Magaña; Victor Barasuol; Marco Camurri; Luca Franceschi 001; Michele Focchi; Massimiliano Pontil; Darwin G. Caldwell; Claudio Semini (IEEE Robotics Autom. Lett., 2019)

On the Iteration Complexity of Hypergradient Computation. - Riccardo Grazzi; Luca Franceschi 001; Massimiliano Pontil; Saverio Salzo (ICML, 2020)

Marthe: Scheduling the Learning Rate Via Online Hypergradients. - Michele Donini; Luca Franceschi 001; Orchid Majumder; Massimiliano Pontil; Paolo Frasconi (IJCAI, 2020)

Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. - Mathias Niepert; Pasquale Minervini; Luca Franceschi 001 (NeurIPS, 2021)

A unified framework for gradient-based hyperparameter optimization and meta-learning. - Luca Franceschi 001 (2021)

ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. - Yihong Chen; Pushkar Mishra; Luca Franceschi 001; Pasquale Minervini; Pontus Stenetorp; Sebastian Riedel 001 (NeurIPS, 2022)

ReFactorGNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. - Yihong Chen; Pushkar Mishra; Luca Franceschi 001; Pasquale Minervini; Pontus Stenetorp; Sebastian Riedel 001 (CoRR, 2022)

Learning Discrete Directed Acyclic Graphs via Backpropagation. - Andrew J. Wren; Pasquale Minervini; Luca Franceschi 001; Valentina Zantedeschi (CoRR, 2022)

Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. - Pasquale Minervini; Luca Franceschi 001; Mathias Niepert (AAAI, 2023)

DAG Learning on the Permutahedron. - Valentina Zantedeschi; Luca Franceschi 001; Jean Kaddour; Matt J. Kusner; Vlad Niculae (ICLR, 2023)

Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". - Mia C. Mayer; Muhammad Bilal Zafar; Luca Franceschi 001; Huzefa Rangwala (KDD, 2023)

Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography. - Luca Franceschi 001; Cemre Zor; Muhammad Bilal Zafar; Gianluca Detommaso; Cédric Archambeau; Tamas Madl; Michele Donini; Matthias W. Seeger (TML4H, 2023)

Explaining Probabilistic Models with Distributional Values. - Luca Franceschi 001; Michele Donini; Cédric Archambeau; Matthias W. Seeger (ICML, 2024)

Evaluating Large Language Models with fmeval. - Pola Schwöbel; Luca Franceschi 001; Muhammad Bilal Zafar; Keerthan Vasist; Aman Malhotra; Tomer Shenhar; Pinal Tailor; Pinar Yilmaz; Michael Diamond; Michele Donini (CoRR, 2024)

Jet Expansions of Residual Computation. - Yihong Chen; Xiangxiang Xu; Yao Lu; Pontus Stenetorp; Luca Franceschi 001 (CoRR, 2024)

Hyperparameter Optimization in Machine Learning. - Luca Franceschi 001; Michele Donini; Valerio Perrone; Aaron Klein; Cédric Archambeau; Matthias W. Seeger; Massimiliano Pontil; Paolo Frasconi (CoRR, 2024)