no code implementations • 4 Jun 2021 • Jason M. Altschuler, Pablo A. Parrilo
Our results are presented for smooth isotropic kernels, the predominant class of kernels used in applications.
1 code implementation • 27 Jan 2021 • Tobia Marcucci, Jack Umenberger, Pablo A. Parrilo, Russ Tedrake
Given a graph, the shortest-path problem requires finding a sequence of edges with minimum cumulative length that connects a source vertex to a target vertex.
Robot Navigation Discrete Mathematics Optimization and Control
1 code implementation • 8 Oct 2019 • Peter M. Larsen, Edward L. Pang, Pablo A. Parrilo, Karsten W. Jacobsen
In computational analysis of Bravais lattices, fulfilment of symmetry conditions is usually determined by analysis of the metric tensor, using either a numerical tolerance to produce a binary (i. e. yes or no) classification, or a distance function which quantifies the deviation from an ideal lattice type.
Materials Science
2 code implementations • 13 Dec 2018 • Diego Cifuentes, Thomas Kahle, Pablo A. Parrilo
The package SOS implements sums-of-squares (SOS) decompositions in Macaulay2.
Optimization and Control Commutative Algebra Primary: 13J30, Secondary: 90C22, 13P25
no code implementations • 12 Jul 2018 • Murat A. Erdogdu, Asuman Ozdaglar, Pablo A. Parrilo, Nuri Denizcan Vanli
Furthermore, incorporating Lanczos method to the block-coordinate maximization, we propose an algorithm that is guaranteed to return a solution that provides $1-O(1/r)$ approximation to the original SDP without any assumptions, where $r$ is the rank of the factorization.
no code implementations • NeurIPS 2017 • Mert Gurbuzbalaban, Asuman Ozdaglar, Pablo A. Parrilo, Nuri Vanli
The coordinate descent (CD) method is a classical optimization algorithm that has seen a revival of interest because of its competitive performance in machine learning applications.
1 code implementation • 2 May 2017 • Hamza Fawzi, James Saunderson, Pablo A. Parrilo
As such, we introduce strategies for constructing semidefinite approximations that we expect will be useful, more generally, for studying the approximation power of functions with small semidefinite representations.
Optimization and Control