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pro vyhledávání: '"Jung, Woosuk L."'
Autor:
Song, Mengmeng, Goncalves, Douglas, Jung, Woosuk L., Lavor, Carlile, Mucherino, Antonio, Wolkowicz, Henry
We consider the nonconvex minimization problem, with quartic objective function, that arises in the exact recovery of a configuration matrix $P\in \Rnd$ of $n$ points when a Euclidean distance matrix, \EDMp, is given with embedding dimension $d$. It
Externí odkaz:
http://arxiv.org/abs/2408.07256
Facial reduction, FR, is a regularization technique for convex programs where the strict feasibility constraint qualification, CQ, fails. Though this CQ holds generically, failure is pervasive in applications such as semidefinite relaxations of hard
Externí odkaz:
http://arxiv.org/abs/2407.06408
We consider the \emph{exact} error correction of a noisy Euclidean distance matrix, EDM, where the elements are the squared distances between $n$ points in $R^d$. For our problem we are given two facts: (i) the embedding dimension, $d$, (ii) \emph{ex
Externí odkaz:
http://arxiv.org/abs/2406.15969
The \emph{simplified} Wasserstein barycenter problem, also known as the cheapest hub problem, consists in selecting one point from each of $k$ given sets, each set consisting of $n$ points, with the aim of minimizing the sum of distances to the baryc
Externí odkaz:
http://arxiv.org/abs/2311.05045
The $\omega$-Condition Number for Optimal Preconditioning and Low Rank Generalized Jacobian Updating
Preconditioning is essential in iterative methods for solving linear systems. It is also the implicit objective in updating approximations of Jacobians in optimization methods, e.g., in quasi-Newton methods. Motivated by the latter, we study a noncla
Externí odkaz:
http://arxiv.org/abs/2308.13195