26 citations · 69 across the 17 of their papers we have counts for
19 papers
Full Convergence of Regularized Methods for Unconstrained Optimization
Andrea Cristofari
Typically, the sequence of points generated by an optimization algorithm may have multiple limit points. Under convexity assumptions, however, (sub)gradient methods are known to ge…
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…
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…
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…
Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
Sara Venturini, Andrea Cristofari, Francesco Rinaldi +1
Clustering (or community detection) on multilayer graphs poses several additional complications with respect to standard graphs as different layers may be characterized by differen…
Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descent
Sara Venturini, Andrea Cristofari, Francesco Rinaldi +1
Graph Semi-Supervised learning is an important data analysis tool, where given a graph and a set of labeled nodes, the aim is to infer the labels to the remaining unlabeled nodes.…
A decomposition method for lasso problems with zero-sum constraint
Andrea Cristofari
In this paper, we consider lasso problems with zero-sum constraint, commonly required for the analysis of compositional data in high-dimensional spaces. A novel algorithm is propos…
Minimization over the l1-ball using an active-set non-monotone projected gradient
Andrea Cristofari, Marianna De Santis, Stefano Lucidi +1
The l1-ball is a nicely structured feasible set that is widely used in many fields (e.g., machine learning, statistics and signal analysis) to enforce some sparsity in the model so…
A Variance-aware Multiobjective Louvain-like Method for Community Detection in Multiplex Networks
Sara Venturini, Andrea Cristofari, Francesco Rinaldi +1
In this paper, we focus on the community detection problem in multiplex networks, i.e., networks with multiple layers having same node sets and no inter-layer connections. In parti…
An augmented Lagrangian method exploiting an active-set strategy and second-order information
Andrea Cristofari, Gianni Di Pillo, Giampaolo Liuzzi +1
In this paper, we consider nonlinear optimization problems with nonlinear equality constraints and bound constraints on the variables. For the solution of such problems, many augme…
Active-set identification with complexity guarantees of an almost cyclic 2-coordinate descent method with Armijo line search
Andrea Cristofari
In this paper, it is established finite active-set identification of an almost cyclic 2-coordinate descent method for problems with one linear coupling constraint and simple bounds…
A derivative-free method for structured optimization problems
Andrea Cristofari, Francesco Rinaldi
Structured optimization problems are ubiquitous in fields like data science and engineering. The goal in structured optimization is using a prescribed set of points, called atoms,…
Total variation based community detection using a nonlinear optimization approach
Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
Maximizing the modularity of a network is a successful tool to identify an important community of nodes. However, this combinatorial optimization problem is known to be NP-complete…
An almost cyclic 2-coordinate descent method for singly linearly constrained problems
Andrea Cristofari
A block decomposition method is proposed for minimizing a (possibly non-convex) continuously differentiable function subject to one linear equality constraint and simple bounds on…
On global minimizers of quadratic functions with cubic regularization
Andrea Cristofari, Tayebeh Dehghan Niri, Stefano Lucidi
In this paper, we analyze some theoretical properties of the problem of minimizing a quadratic function with a cubic regularization term, arising in many methods for unconstrained…
An Active-Set Algorithmic Framework for Non-Convex Optimization Problems over the Simplex
Andrea Cristofari, Marianna De Santis, Stefano Lucidi +1
In this paper, we describe a new active-set algorithmic framework for minimizing a non-convex function over the unit simplex. At each iteration, the method makes use of a rule for…
Data Filtering for Cluster Analysis by -Norm Regularization
Andrea Cristofari
A data filtering method for cluster analysis is proposed, based on minimizing a least squares function with a weighted -norm penalty. To overcome the discontinuity of the o…
A Two-Stage Active-Set Algorithm for Bound-Constrained Optimization
Andrea Cristofari, Marianna De Santis, Stefano Lucidi +1
In this paper, we describe a two-stage method for solving optimization problems with bound constraints. It combines the active-set estimate described in [Facchinei and Lucidi, 1995…