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 "optimal pricing for mhr and lambda regular distributions"):
  Abstract: We study the performance of anonymous posted-price selling mechanisms for a standard Bayesian auction setting, where $n$ bidders have i.i.d. valuations for a single item. We show that for the natural class of Monotone Hazard Rate (MHR) distributions, offering the same, take-it-or-leave-it price to all bidders can achieve an (asymptotically) optimal revenue. In particular, the approximation ratio is shown to be $1+O(\ln \ln n/\ln n)$, matched by a tight lower bound for the case of exponential distributions. This improves upon the previously best-known upper bound of $e/(e-1)\approx 1.58$ for the slightly more general class of regular distributions. In the worst case (over $n$), we still show a global upper bound of $1.35$. We give a simple, closed-form description of our prices which, interestingly enough, relies only on minimal knowledge of the prior distribution, namely just the expectation of its second-highest order statistic. #R##N#Furthermore, we extend our techniques to handle the more general class of $\lambda$-regular distributions that interpolate between MHR ($\lambda=0$) and regular ($\lambda=1$). Our anonymous pricing rule now results in an asymptotic approximation ratio that ranges smoothly, with respect to $\lambda$, from $1$ (MHR distributions) to $e/(e-1)$ (regular distributions). Finally, we explicitly give a class of continuous distributions that provide matching lower bounds, for every $\lambda$.

Includes members:
  Member "optimal auctions vs anonymous pricing beyond linear utility":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simple mechanisms for non linear agents")
  Member "optimal pricing for mhr distributions":
    also connected through other hyperedges:
      (none)
  Member "tight revenue gaps among simple mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "tight approximation ratio of anonymous pricing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "prophet secretary for combinatorial auctions and matroids":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "online market intermediation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient two sided markets with limited information")
  Member "revenue gaps for discriminatory and anonymous sequential posted pricing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tight revenue gaps among simple mechanisms")
  Member "revenue gaps for static and dynamic posted pricing of homogeneous goods":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "tight revenue gaps among simple mechanisms")

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)