Semidefinite programming relaxations for quantum correlations
Semidefinite programs are convex optimization problems involving a linear objective
function and a domain of positive-semidefinite matrices. Over the past two decades, they …
function and a domain of positive-semidefinite matrices. Over the past two decades, they …
Computational intelligence in wireless sensor networks: A survey
RV Kulkarni, A Förster… - … surveys & tutorials, 2010 - ieeexplore.ieee.org
Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can
sense or monitor physical or environmental conditions cooperatively. WSNs face many …
sense or monitor physical or environmental conditions cooperatively. WSNs face many …
[图书][B] Variational analysis and applications
BS Mordukhovich - 2018 - Springer
Boris S. Mordukhovich Page 1 Springer Monographs in Mathematics Boris S. Mordukhovich
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Convex relaxation of optimal power flow—Part I: Formulations and equivalence
SH Low - IEEE Transactions on Control of Network Systems, 2014 - ieeexplore.ieee.org
This tutorial summarizes recent advances in the convex relaxation of the optimal power flow
(OPF) problem, focusing on structural properties rather than algorithms. Part I presents two …
(OPF) problem, focusing on structural properties rather than algorithms. Part I presents two …
Zero duality gap in optimal power flow problem
The optimal power flow (OPF) problem is nonconvex and generally hard to solve. In this
paper, we propose a semidefinite programming (SDP) optimization, which is the dual of an …
paper, we propose a semidefinite programming (SDP) optimization, which is the dual of an …
[图书][B] Handbook of satisfiability
“Satisfiability (SAT) related topics have attracted researchers from various disciplines: logic,
applied areas such as planning, scheduling, operations research and combinatorial …
applied areas such as planning, scheduling, operations research and combinatorial …
Robust optimization
Robust Optimization Page 1 Page 2 Robust Optimization Page 3 Princeton Series in Applied
Mathematics Series Editors: Ingrid Daubechies (Princeton University); Weinan E (Princeton …
Mathematics Series Editors: Ingrid Daubechies (Princeton University); Weinan E (Princeton …
[图书][B] Convex optimization
S Boyd, L Vandenberghe - 2004 - books.google.com
Convex optimization problems arise frequently in many different fields. This book provides a
comprehensive introduction to the subject, and shows in detail how such problems can be …
comprehensive introduction to the subject, and shows in detail how such problems can be …
Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
The affine rank minimization problem consists of finding a matrix of minimum rank that
satisfies a given system of linear equality constraints. Such problems have appeared in the …
satisfies a given system of linear equality constraints. Such problems have appeared in the …
Fast linear iterations for distributed averaging
We consider the problem of finding a linear iteration that yields distributed averaging
consensus over a network, ie, that asymptotically computes the average of some initial …
consensus over a network, ie, that asymptotically computes the average of some initial …