human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "efficiency of revenue optimal mechanisms"
  Abstract: We compare the expected efficiency of revenue maximizing (or {\em optimal}) mechanisms with that of efficiency maximizing ones. We show that the efficiency of the revenue maximizing mechanism for selling a single item with k + log_{e/(e-1)} k + 1 bidders is at least as much as the efficiency of the efficiency maximizing mechanism with k bidders, when bidder valuations are drawn i.i.d. from a Monotone Hazard Rate distribution. Surprisingly, we also show that this bound is tight within a small additive constant of 5.7. In other words, Theta(log k) extra bidders suffice for the revenue maximizing mechanism to match the efficiency of the efficiency maximizing mechanism, while o(log k) do not. This is in contrast to the result of Bulow and Klemperer comparing the revenue of the two mechanisms, where only one extra bidder suffices. More precisely, they show that the revenue of the efficiency maximizing mechanism with k+1 bidders is no less than the revenue of the revenue maximizing mechanism with k bidders. #R##N#We extend our result for the case of selling t identical items and show that 2.2 log k + t Theta(log log k) extra bidders suffice for the revenue maximizing mechanism to match the efficiency of the efficiency maximizing mechanism. #R##N#In order to prove our results, we do a classification of Monotone Hazard Rate (MHR) distributions and identify a family of MHR distributions, such that for each class in our classification, there is a member of this family that is pointwise lower than every distribution in that class. This lets us prove interesting structural theorems about distributions with Monotone Hazard Rate.

Connected through hyperedge HE-1 (induced by source paper "reserve pricing in repeated second price auctions with strategic bidders"):
  with members:
    - "dynamic reserve prices for repeated auctions learning from bids"
    - "optimal pricing in repeated posted price auctions"
    - "learning optimal reserve price against non myopic bidders"
    - "contextual search via intrinsic volumes"
    - "robust repeated auctions under heterogeneous buyer behavior"
    - "optimal dynamic auctions are virtual welfare maximizers"
    - "dynamic pricing with finitely many unknown valuations"
    - "on consistency of optimal pricing algorithms in repeated posted price auctions with strategic buyer"

Connected through hyperedge HE-2 (induced by source paper "optimal pricing for mhr and lambda regular distributions"):
  with members:
    - "optimal auctions vs anonymous pricing beyond linear utility"
    - "optimal pricing for mhr distributions"
    - "tight revenue gaps among simple mechanisms"
    - "tight approximation ratio of anonymous pricing"
    - "prophet secretary for combinatorial auctions and matroids"
    - "online market intermediation"
    - "revenue gaps for discriminatory and anonymous sequential posted pricing"
    - "revenue gaps for static and dynamic posted pricing of homogeneous goods"

Connected through hyperedge HE-3 (induced by source paper "on the ratio of revenue to welfare in single parameter mechanism design"):
  with members:
    - "efficiency loss in revenue optimal auctions"

Connected through hyperedge HE-4 (induced by source paper "efficiency revenue trade offs in auctions"):
  with members:
    - "how good is the chord algorithm"
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"
    - "optimal auctions with correlated bidders are easy"
    - "efficiency loss in revenue optimal auctions"

Connected through hyperedge HE-5 (induced by source paper "efficiency loss in revenue optimal auctions"):
  with members:
    - "revenue optimal auction for single minded buyers"

Question: Please tell me which class the center node 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)