2 code implementations • 14 Sep 2023 • Rajiv Sambharya, Georgina Hall, Brandon Amos, Bartolomeo Stellato
We introduce a machine-learning framework to warm-start fixed-point optimization algorithms.
no code implementations • 11 May 2021 • Amir Ali Ahmadi, Cemil Dibek, Georgina Hall
We establish that the answer to question (i) is positive for univariate plus quadratic polynomials and for convex SPQ polynomials, but negative already for bivariate quartic SPQ polynomials.
no code implementations • 1 Jul 2020 • Georgina Hall, Laurent Massoulié
Our focus here is on partial recovery, i. e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\H{o}s-R\'enyi graphs of parameters $(n, q, s)$.
no code implementations • 14 Aug 2019 • Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi
Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics.
no code implementations • 16 Jun 2018 • Amir Ali Ahmadi, Georgina Hall
As a byproduct, our proof shows that the problem of testing whether all matrices in an interval family are positive semidefinite is strongly NP-hard.
no code implementations • 22 Nov 2016 • Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani
Motivated by applications in robotics and computer vision, we study problems related to spatial reasoning of a 3D environment using sublevel sets of polynomials.
no code implementations • 6 Oct 2015 • Amir Ali Ahmadi, Georgina Hall
We consider the problem of decomposing a multivariate polynomial as the difference of two convex polynomials.