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pro vyhledávání: '"Hall, Georgina"'
We introduce a machine-learning framework to warm-start fixed-point optimization algorithms. Our architecture consists of a neural network mapping problem parameters to warm starts, followed by a predefined number of fixed-point iterations. We propos
Externí odkaz:
http://arxiv.org/abs/2309.07835
First-order methods are widely used to solve convex quadratic programs (QPs) in real-time applications because of their low per-iteration cost. However, they can suffer from slow convergence to accurate solutions. In this paper, we present a framewor
Externí odkaz:
http://arxiv.org/abs/2212.08260
We study separable plus quadratic (SPQ) polynomials, i.e., polynomials that are the sum of univariate polynomials in different variables and a quadratic polynomial. Motivated by the fact that nonnegative separable and nonnegative quadratic polynomial
Externí odkaz:
http://arxiv.org/abs/2105.04766
Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, or verifying sustainable supplier practices. Initiatives leading the implementation of traceability technologies must choose th
Externí odkaz:
http://arxiv.org/abs/2104.14818
Autor:
Hall, Georgina, Massoulié, Laurent
In this paper, we consider the graph alignment problem, which is the problem of recovering, given two graphs, a one-to-one mapping between nodes that maximizes edge overlap. This problem can be viewed as a noisy version of the well-known graph isomor
Externí odkaz:
http://arxiv.org/abs/2007.00533
Autor:
Curmei, Mihaela, Hall, Georgina
We present a hierarchy of semidefinite programs (SDPs) for the problem of fitting a shape-constrained (multivariate) polynomial to noisy evaluations of an unknown shape-constrained function. These shape constraints include convexity or monotonicity o
Externí odkaz:
http://arxiv.org/abs/2004.03853
Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this paper, we survey recent approaches for addressing this challenge includi
Externí odkaz:
http://arxiv.org/abs/1908.05209
Autor:
Hall, Georgina
Optimizing over the cone of nonnegative polynomials, and its dual counterpart, optimizing over the space of moments that admit a representing measure, are fundamental problems that appear in many different applications from engineering and computatio
Externí odkaz:
http://arxiv.org/abs/1906.07961
Akademický článek
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Autor:
Hall, Georgina
The problem of optimizing over the cone of nonnegative polynomials is a fundamental problem in computational mathematics, with applications to polynomial optimization, control, machine learning, game theory, and combinatorics, among others. A number
Externí odkaz:
http://arxiv.org/abs/1806.06996