3 papers
math.OC2026
Objective-Function Free Multi-Objective Optimization: Rate of Convergence and Performance of an Adagrad-like algorithm
Marianna De Santis, Gabriele Eichfelder, Margherita Porcelli
We propose an Adagrad-like algorithm for multi-objective unconstrained optimization that relies on the computation of a common descent direction only. Unlike classical local algori…
math.OC2025
Worst-Case Complexity of High-Order Algorithms for Pareto-Front Reconstruction
Andrea Cristofari, Marianna De Santis, Stefano Lucidi +1
In this paper, we are concerned with a worst-case complexity analysis of a-posteriori algorithms for unconstrained multiobjective optimization. Specifically, we propose an algorith…
cs.LG2023
Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization
Sara Venturini, Marianna de Santis, Jordan Patracone +3
In recent years, bilevel approaches have become very popular to efficiently estimate high-dimensional hyperparameters of machine learning models. However, to date, binary parameter…