Giovanni De Toni

According to our database, Giovanni De Toni authored at least 10 papers between 2020 and 2024.

Collaborative distances:

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

2024

Personalized Algorithmic Recourse with Preference Elicitation.

Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini

Trans. Mach. Learn. Res., 2024

Time Can Invalidate Algorithmic Recourse.

Giovanni De Toni, Stefano Teso, Bruno Lepri, Andrea Passerini

CoRR, 2024

Towards Human-AI Complementarity with Predictions Sets.

Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez-Rodriguez

CoRR, 2024

Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration.

Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro

CoRR, 2024

Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration.

Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro

Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 2024

2023

Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis.

Giovanni De Toni, Bruno Lepri, Andrea Passerini

Mach. Learn., April, 2023

2022

Generating personalized counterfactual interventions for algorithmic recourse by eliciting user preferences.

Giovanni De Toni, Paolo Viappiani, Bruno Lepri, Andrea Passerini

CoRR, 2022

2021

Learning compositional programs with arguments and sampling.

Giovanni De Toni, Luca Erculiani, Andrea Passerini

CoRR, 2021

2020

Pyglmnet: Python implementation of elastic-net regularized generalized linear models.

Mainak Jas, Titipat Achakulvisut, Aid Idrizovic, Daniel E. Acuna, Matthew Antalek, Vinícius Marques, Tommy Odland, Ravi Garg, Mayank Agrawal, Yu Umegaki, Peter Foley, Hugo Fernandes, Drew Harris, Beibin Li, Olivier Pieters, Scott Otterson, Giovanni De Toni, Chris C. Rodgers, Eva L. Dyer, Matti S. Hämäläinen, Konrad P. Körding, Pavan Ramkumar

J. Open Source Softw., 2020

A general method for estimating the prevalence of Influenza-Like-Symptoms with Wikipedia data.

Giovanni De Toni, Cristian Consonni, Alberto Montresor

CoRR, 2020