human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "algorithms for destructive shift bribery"):
  Abstract: We study the complexity of Destructive Shift Bribery. In this problem, we are given an election with a set of candidates and a set of voters (each ranking the candidates from the best to the worst), a despised candidate $d$, a budget $B$, and prices for shifting $d$ back in the voters' rankings. The goal is to ensure that $d$ is not a winner of the election. We show that this problem is polynomial-time solvable for scoring protocols (encoded in unary), the Bucklin and Simplified Bucklin rules, and the Maximin rule, but is NP-hard for the Copeland rule. This stands in contrast to the results for the constructive setting (known from the literature), for which the problem is polynomial-time solvable for $k$-Approval family of rules, but is NP-hard for the Borda, Copeland, and Maximin rules. We complement the analysis of the Copeland rule showing W-hardness for the parameterization by the budget value, and by the number of affected voters. We prove that the problem is W-hard when parameterized by the number of voters even for unit prices. From the positive perspective we provide an efficient algorithm for solving the problem parameterized by the combined parameter the number of candidates and the maximum bribery price (alternatively the number of different bribery prices).

Includes members:
  Member "robustness among multiwinner voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "matchings under preferences strength of stability and trade offs")
  Member "voting and bribing in single exponential time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "n fold integer programming via lp rounding")
  Member "on the hardness of bribery variants in voting with cp nets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal bribery in voting")
  Member "prices matter for the parameterized complexity of shift bribery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal bribery in voting")
  Member "estimating the margin of victory of an election using sampling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minimizing margin of victory for fair political and educational districting")
  Member "campaign management under approval driven voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximation and hardness of shift bribery")
  Member "properties of multiwinner voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "who is in your top three optimizing learning in elections with many candidates")
  Member "complexity of manipulation bribery and campaign management in bucklin and fallback voting":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal bribery in voting")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.AI(Artificial Intelligence)