scholarly journals Polynomial-Time Algorithm for Simulation of Weakly Interacting Quantum Spin Systems

2008 ◽  
Vol 284 (2) ◽  
pp. 481-507 ◽  
Author(s):  
Sergey Bravyi ◽  
David DiVincenzo ◽  
Daniel Loss
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.


2006 ◽  
Vol 269 (3) ◽  
pp. 611-657 ◽  
Author(s):  
Marek Biskup ◽  
Lincoln Chayes ◽  
Shannon Starr

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