Leonardo Cella

According to our database1, Leonardo Cella authored at least 27 papers between 2017 and 2024.

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Bibliography

2024
Distribution-free Inferential Models: Achieving finite-sample valid probabilistic inference, with emphasis on quantile regression.
Int. J. Approx. Reason., 2024

Variational Approximations of Possibilistic Inferential Models.
Proceedings of the Belief Functions: Theory and Applications, 2024

Fusing Independent Inferential Models in a Black-Box Manner.
Proceedings of the Belief Functions: Theory and Applications, 2024

2023
Possibility-theoretic statistical inference offers performance and probativeness assurances.
Int. J. Approx. Reason., December, 2023

Finite sample valid probabilistic inference on quantile regression.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

Multi-task Representation Learning with Stochastic Linear Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Direct and approximately valid probabilistic inference on a class of statistical functionals.
Int. J. Approx. Reason., 2022

Valid inferential models for prediction in supervised learning problems.
Int. J. Approx. Reason., 2022

Validity, consonant plausibility measures, and conformal prediction.
Int. J. Approx. Reason., 2022

Meta Representation Learning with Contextual Linear Bandits.
CoRR, 2022

Multi-task Representation Learning with Stochastic Linear Bandits.
CoRR, 2022

Group Meritocratic Fairness in Linear Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Valid Inferential Models Offer Performance and Probativeness Assurances.
Proceedings of the Belief Functions: Theory and Applications, 2022

2021
Multi-task and meta-learning with sparse linear bandits.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Best Model Identification: A Rested Bandit Formulation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Approximately Valid and Model-Free Possibilistic Inference.
Proceedings of the Belief Functions: Theory and Applications, 2021

2020
Online Model Selection: a Rested Bandit Formulation.
CoRR, 2020

Meta-learning with Stochastic Linear Bandits.
Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Bandits with Delay-Dependent Payoffs.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Incorporating Expert Opinion in an Inferential Model while Maintaining Validity.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Efficient Linear Bandits through Matrix Sketching.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Efficient Context-Aware Sequential Recommender System.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

2017
Deriving Item Features Relevance from Past User Interactions.
Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

Modelling User Behaviors with Evolving Users and Catalogs of Evolving Items.
Proceedings of the Adjunct Publication of the 25th Conference on User Modeling, 2017

Exploring the Semantic Gap for Movie Recommendations.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Kernalized Collaborative Contextual Bandits.
Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017), 2017

Estimate Features Relevance for Groups of Users.
Proceedings of the 8th Italian Information Retrieval Workshop, 2017


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