A Polynomial Time Algorithm in General Quadratic Programming and Ground-State Properties of Spin Glasses

1986 ◽  
Vol 1 (7) ◽  
pp. 319-326 ◽  
Author(s):  
J Canisius ◽  
J. L. van Hemmen
2015 ◽  
Vol 11 (7) ◽  
pp. 566-569 ◽  
Author(s):  
Zeph Landau ◽  
Umesh Vazirani ◽  
Thomas Vidick

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.


2002 ◽  
Vol 50 (8) ◽  
pp. 1935-1941 ◽  
Author(s):  
Dongning Li ◽  
Yong Ching Lim ◽  
Yong Lian ◽  
Jianjian Song

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