From the 1 of 5 linked papers with an AI index.
5 papers
Full Convergence of Regularized Methods for Unconstrained Optimization
Andrea Cristofari
The paper shows that unconstrained optimization algorithms using locally quadratic models regularized by a high‑order norm term generate a fully convergent sequence of iterates for…
Block cubic Newton with greedy selection
Andrea Cristofari
A second-order block coordinate descent method is proposed for the unconstrained minimization of an objective function with a Lipschitz continuous Hessian. At each iteration, a blo…
Complexity results and active-set identification of a derivative-free method for bound-constrained problems
Andrea Brilli, Andrea Cristofari, Giampaolo Liuzzi +1
In this paper, we analyze a derivative-free line search method designed for bound-constrained problems. Our analysis demonstrates that this method exhibits a worst-case complexity…
Probabilistic Iterative Hard Thresholding for Sparse Learning
Matteo Bergamaschi, Andrea Cristofari, Vyacheslav Kungurtsev +1
For statistical modeling wherein the data regime is unfavorable in terms of dimensionality relative to the sample size, finding hidden sparsity in the ground truth can be critical…
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…