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Compressed sensing off the grid
This paper investigates the problem of estimating the frequency components of a mixture of
s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous …
s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous …
On implementing a primal-dual interior-point method for conic quadratic optimization
Based on the work of the Nesterov and Todd on self-scaled cones an implementation of a
primal-dual interior-point method for solving large-scale sparse conic quadratic optimization …
primal-dual interior-point method for solving large-scale sparse conic quadratic optimization …
Interior point methods for nonlinear optimization
Interior-point methods (IPMs) are among the most efficient methods for solving linear, and
also wide classes of other convex optimization problems. Since the path-breaking work of …
also wide classes of other convex optimization problems. Since the path-breaking work of …
[کتاب][B] Aspects of semidefinite programming: interior point algorithms and selected applications
E De Klerk - 2006 - books.google.com
Semidefinite programming has been described as linear programming for the year 2000. It is
an exciting new branch of mathematical programming, due to important applications in …
an exciting new branch of mathematical programming, due to important applications in …
Semidefinite optimization
Optimization problems in which the variable is not a vector but a symmetric matrix which is
required to be positive semidefinite have been intensely studied in the last ten years. Part of …
required to be positive semidefinite have been intensely studied in the last ten years. Part of …
Interior-point methods for optimization
This article describes the current state of the art of interior-point methods (IPMs) for convex,
conic, and general nonlinear optimization. We discuss the theory, outline the algorithms, and …
conic, and general nonlinear optimization. We discuss the theory, outline the algorithms, and …
Robust convex approximation methods for TDOA-based localization under NLOS conditions
In this paper, we develop a novel robust optimization approach to source localization using
time-difference-of-arrival (TDOA) measurements that are collected under non-line-of-sight …
time-difference-of-arrival (TDOA) measurements that are collected under non-line-of-sight …
Semidefinite programming for combinatorial optimization
C Helmberg - 2000 - opus4.kobv.de
This book offers a self-contained introduction to the field of semidefinite programming, its
applications in combinatorial optimization, and its computational methods. We equip the …
applications in combinatorial optimization, and its computational methods. We equip the …
Analyzing developer sentiment in commit logs
The paper presents an analysis of developer commit logs for GitHub projects. In particular,
developer sentiment in commits is analyzed across 28,466 projects within a seven year time …
developer sentiment in commits is analyzed across 28,466 projects within a seven year time …
[PDF][PDF] The CVXOPT linear and quadratic cone program solvers
The CVXOPT linear and quadratic cone program solvers Page 1 The CVXOPT linear and
quadratic cone program solvers L. Vandenberghe March 20, 2010 Abstract This document …
quadratic cone program solvers L. Vandenberghe March 20, 2010 Abstract This document …