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Recent scalability improvements for semidefinite programming with applications in machine learning, control, and robotics
Historically, scalability has been a major challenge for the successful application of
semidefinite programming in fields such as machine learning, control, and robotics. In this …
semidefinite programming in fields such as machine learning, control, and robotics. In this …
Multiresolution Markov models for signal and image processing
Reviews a significant component of the rich field of statistical multiresolution (MR) modeling
and processing. These MR methods have found application and permeated the literature of …
and processing. These MR methods have found application and permeated the literature of …
A survey of relaxations and approximations of the power flow equations
The power flow equations relate the power injections and voltages in an electric power
system and are therefore key to many power system optimization and control problems …
system and are therefore key to many power system optimization and control problems …
Convex relaxation of optimal power flow—Part I: Formulations and equivalence
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 …
Distributed optimal power flow for smart microgrids
Optimal power flow (OPF) is considered for microgrids, with the objective of minimizing
either the power distribution losses, or, the cost of power drawn from the substation and …
either the power distribution losses, or, the cost of power drawn from the substation and …
Convex relaxations and linear approximation for optimal power flow in multiphase radial networks
Distribution networks are usually multiphase and radial. To facilitate power flow computation
and optimization, two semidefinite programming (SDP) relaxations of the optimal power flow …
and optimization, two semidefinite programming (SDP) relaxations of the optimal power flow …
[ספר][B] Graphs and matrices
RB Bapat - 2010 - Springer
This book is concerned with results in graph theory in which linear algebra and matrix theory
play an important role. Although it is generally accepted that linear algebra can be an …
play an important role. Although it is generally accepted that linear algebra can be an …
Matrix estimation by universal singular value thresholding
S Chatterjee - 2015 - projecteuclid.org
Consider the problem of estimating the entries of a large matrix, when the observed entries
are noisy versions of a small random fraction of the original entries. This problem has …
are noisy versions of a small random fraction of the original entries. This problem has …
Euclidean distance geometry and applications
Euclidean distance geometry is the study of Euclidean geometry based on the concept of
distance. This is useful in several applications where the input data consist of an incomplete …
distance. This is useful in several applications where the input data consist of an incomplete …
[ספר][B] Linear matrix inequalities in system and control theory
S Boyd, L El Ghaoui, E Feron, V Balakrishnan - 1994 - SIAM
The basic topic of this book is solving problems from system and control theory using convex
optimization. We show that a wide variety of problems arising in system and control theory …
optimization. We show that a wide variety of problems arising in system and control theory …