CANDELIERI ANTONIO

Candelieri, A., Ponti, A., Archetti, F. (2025). Multi-Objective and Multiple Information Source Optimization for Fair & Green Machine Learning. In Numerical Computations: Theory and Algorithms 4th International Conference, NUMTA 2023, Pizzo Calabro, Italy, June 14–20, 2023, Revised Selected Papers, Part I (pp.49-63). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-81241-5_4]. Detail

Candelieri, A., Signori, E. (2025). MLE-Free Gaussian Process Based Bayesian Optimization. In Learning and Intelligent Optimization 18th International Conference, LION 18, Ischia Island, Italy, June 9–13, 2024, Revised Selected Papers (pp.81-95). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-75623-8_7]. Detail

Candelieri, A., Ponti, A., Archetti, F. (2025). Gaussian Process regression over discrete probability measures: on the non-stationarity relation between Euclidean and Wasserstein Squared Exponential Kernels. JOURNAL OF GLOBAL OPTIMIZATION [10.1007/s10898-025-01463-y]. Detail

Candelieri, A. (2025). Resource Allocation via Bayesian Optimization: an Efficient Alternative to Semi-Bandit Feedback. In Numerical Computations: Theory and Algorithms 4th International Conference, NUMTA 2023, Pizzo Calabro, Italy, June 14–20, 2023, Revised Selected Papers, Part I (pp.34-48). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-81241-5_3]. Detail

Candelieri, A., Ponti, A., Archetti, F. (2025). A Constrained-JKO Scheme for Effective and Efficient Wasserstein Gradient Flows. In Learning and Intelligent Optimization 18th International Conference, LION 18, Ischia Island, Italy, June 9–13, 2024, Revised Selected Papers (pp.66-80). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-75623-8_6]. Detail