activity
20162022
most citedRandom projections for trust region subproblems

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

math.OC2022

Comparing perspective reformulations for piecewise-convex optimization

Renan Spencer Trindade, Claudia D'Ambrosio, Antonio Frangioni +1

Our study is motivated by the solution of Mixed-Integer Non-Linear Programming (MINLP) problems with separable non-convex functions via the Sequential Convex MINLP technique, an it…

math.OC2020

Learning Discontinuous Piecewise Affine Fitting Functions using Mixed Integer Programming for Segmentation and Denoising

Ruobing Shen, Bo Tang, Leo Liberti +2

Piecewise affine functions are widely used to approximate nonlinear and discontinuous functions. However, most, if not all existing models only deal with fitting continuous functio…

math.OC2018

Strong Convex Nonlinear Relaxations of the Pooling Problem

James Luedtke, Claudia D'Ambrosio, Jeff Linderoth +1

We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which input materials are mixed in intermediate pools, with the ou…

math.OC20172 cited

Random projections for trust region subproblems

Ky Vu, Pierre-Louis Poirion, Claudia D'Ambrosio +1

The trust region method is an algorithm traditionally used in the field of derivative free optimization. The method works by iteratively constructing surrogate models (often linear…

cs.CG2016

New error measures and methods for realizing protein graphs from distance data

Claudia D'Ambrosio, Ky Vu, Carlile Lavor +2

The interval Distance Geometry Problem (iDGP) consists in finding a realization in of a simple undirected graph with nonnegative intervals assigned to the…