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Subspace Acceleration For Large-Scale Parameter-Dependent Hermitian Eigenproblems

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Dynamic Facility Location via Exponential Clocks

Ola Nils Anders Svensson, Ashkan Norouzi Fard, Hyung Chan An

The dynamic facility location problem is a generalization of the classic facility location problem proposed by Eisenstat, Mathieu, and Schabanel to model the dynamics of evolving social/infrastructure networks. The generalization lies in that the distance ...

Association for Computing Machinery2017

Applications of Strong Convex Relaxations to Allocation Problems

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Approximation algorithms are a commonly used tool for designing efficient algorithmic solutions for intractable problems, at the expense of the quality of the output solution. A prominent technique for designing such algorithms is the use of Linear Program ...

EPFL2017

Low-rank methods for parameter-dependent eigenvalue problems and matrix equations

Petar Sirkovic

The focus of this thesis is on developing efficient algorithms for two important problems arising in model reduction, estimation of the smallest eigenvalue for a parameter-dependent Hermitian matrix and solving large-scale linear matrix equations, by extra ...

EPFL2016

A Bi-Criteria Approximation Algorithm for k-Means

Justin Dean Ward

We consider the classical k-means clustering problem in the setting of bi-criteria approximation, in which an algorithm is allowed to output beta*k > k clusters, and must produce a clustering with cost at most alpha times the to the cost of the optimal set ...

Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik2016

MATHICSE Technical Report : Subspace acceleration for large-scale parameter-dependent Hermitian eigenproblems

Daniel Kressner, Petar Sirkovic

This work is concerned with approximating the smallest eigenvalue of a parameter-dependent Hermitian matrix A(μ) for many parameter values μ ∈ RP. The design of reliable and efficient algorithms for addressing this task is of importance in a variety of app ...

MATHICSE2015

Comparing genomes with rearrangements and segmental duplications

Bernard Moret, Mingfu Shao

Motivation: Large-scale evolutionary events such as genomic rearrange. ments and segmental duplications form an important part of the evolution of genomes and are widely studied from both biological and computational perspectives. A basic computational pro ...

Oxford University Press2015

Low rank differential equations for Hamiltonian matrix nearness problems

Daniel Kressner

For a Hamiltonian matrix with purely imaginary eigenvalues, we aim to determine the nearest Hamiltonian matrix such that some or all eigenvalues leave the imaginary axis. Conversely, for a Hamiltonian matrix with all eigenvalues lying off the imaginary axi ...

Springer Heidelberg2015

Efficient Subnetwork Selection in Relay Networks

Christina Fragouli, Siddhartha Brahma, Ayan Sengupta

We consider a source that would like to communicate with a destination over a layered Gaussian relay network. We present a computationally efficient method that enables to select a near-optimal (in terms of throughput) subnetwork of a given size connecting ...

2014

Efficient Subnetwork Selection in Relay Networks

Christina Fragouli, Siddhartha Brahma, Ayan Sengupta

Ieee2014

LP-Based Algorithms for Capacitated Facility Location

Ola Nils Anders Svensson, Hyung Chan An

Linear programming has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of algorithmic methodo ...

IEEE2014