Andere Kunden interessierten sich auch für
![Generalized Low Rank Models]( "Generalized Low Rank Models")
Generalized Low Rank Models95,99 €![Rank-Metric Codes and Their Applications]( "Rank-Metric Codes and Their Applications")
Rank-Metric Codes and Their Applications104,99 €![User Interface Design for Low-literate and Novice Users]( "User Interface Design for Low-literate and Novice Users")
User Interface Design for Low-literate and Novice Users69,99 €![Learning to Rank for Information Retrieval]( "Learning to Rank for Information Retrieval")
Learning to Rank for Information Retrieval89,99 €![Low-Code/No-Code]( "Low-Code/No-Code")
Low-Code/No-Code20,99 €![Rank booster Physics-Jee]( "Rank booster Physics-Jee")
Rank booster Physics-Jee46,99 €![Energy Systems Design for Low-Power Computing]( "Energy Systems Design for Low-Power Computing")
Energy Systems Design for Low-Power Computing198,99 €
Finding low-rank solutions of semidefinite programs is important in many applications. For example, semidefinite programs that arise as relaxations of polynomial optimization problems are exact relaxations when the semidefinite program has a rank-1 solution. Unfortunately, computing a minimum-rank solution of a semidefinite program is an NP-hard problem. This monograph reviews the theory of low-rank semidefinite programming, presenting theorems that guarantee the existence of a low-rank solution, heuristics for computing low-rank solutions, and algorithms for finding low-rank approximate solutions. It then presents applications of the theory to trust-region problems and signal processing.