Search Results for author: Pablo A. Parrilo

Found 7 papers, 4 papers with code

Kernel approximation on algebraic varieties

no code implementations4 Jun 2021 Jason M. Altschuler, Pablo A. Parrilo

Our results are presented for smooth isotropic kernels, the predominant class of kernels used in applications.

Shortest Paths in Graphs of Convex Sets

1 code implementation27 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

Minimum-Strain Symmetrization of Bravais Lattices

1 code implementation8 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

Sums of squares in Macaulay2

2 code implementations13 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

Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs

no code implementations12 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.

Community Detection

When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent

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.

Semidefinite approximations of the matrix logarithm

1 code implementation2 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

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