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 "fair allocation of indivisible goods improvement and generalization"):
  Abstract: We study the problem of fair allocation for indivisible goods. We use the the maxmin share paradigm introduced by Budish as a measure for fairness. Procacciafirst (EC'14) were first to investigate this fundamental problem in the additive setting. In contrast to what real-world experiments suggest, they show that a maxmin guarantee (1-$\MMS$ allocation) is not always possible even when the number of agents is limited to 3. While the existence of an approximation solution (e.g. a $1/2$-$\MMS$ allocation) is quite straightforward, improving the guarantee becomes subtler for larger constants. Procaccia provide a proof for existence of a $2/3$-$\MMS$ allocation and leave the question open for better guarantees. #R##N#Our main contribution is an answer to the above question. We improve the result of \procacciafirst\! to a $3/4$ factor in the additive setting. The main idea for our $3/4$-$\MMS$ allocation method is clustering the agents. To this end, we introduce three notions and techniques, namely reducibility, matching allocation, and cycle-envy-freeness, and prove the approximation guarantee of our algorithm via non-trivial applications of these techniques. Our analysis involves coloring and double counting arguments that might be of independent interest. #R##N#One major shortcoming of the current studies on fair allocation is the additivity assumption on the valuations. We alleviate this by extending our results to the case of submodular, fractionally subadditive, and subadditive settings. More precisely, we give constant approximation guarantees for submodular and XOS agents, and a logarithmic approximation for the case of subadditive agents. Furthermore, we complement our results by providing close upper bounds for each class of valuation functions. Finally, we present algorithms to find such allocations for additive, submodular, and XOS settings in polynomial time.

Includes members:
  Member "fair allocation of indivisible goods to asymmetric agents":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "maximin fairness with mixed divisible and indivisible goods")
  Member "approximation algorithms for computing maximin share allocations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "maximin fairness with mixed divisible and indivisible goods")
  Member "approximate maximin shares for groups of agents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "maximin fairness with mixed divisible and indivisible goods")
  Member "combinatorial algorithm for restricted max min fair allocation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating nash social welfare under submodular valuations through un matchings")
  Member "combinatorial auctions via posted prices":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "bayesian games and the smoothness framework":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the price of anarchy in auctions")
  Member "constrained non monotone submodular maximization offline and secretary algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "submodular matroid secretary problem with shortlists")
  Member "on allocating goods to maximize fairness":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "weighted completion time minimization for unrelated machines via iterative fair contention resolution")

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.GT(Computer Science and Game Theory)