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: "algorithms as mechanisms the price of anarchy of relax and round"
  Abstract: Many algorithms that are originally designed without explicitly considering incentive properties are later combined with simple pricing rules and used as mechanisms. The resulting mechanisms are often natural and simple to understand. But how good are these algorithms as mechanisms? Truthful reporting of valuations is typically not a dominant strategy (certainly not with a pay-your-bid, first-price rule, but it is likely not a good strategy even with a critical value, or second-price style rule either). Our goal is to show that a wide class of approximation algorithms yields this way mechanisms with low Price of Anarchy. #R##N#The seminal result of Lucier and Borodin [SODA 2010] shows that combining a greedy algorithm that is an $\alpha$-approximation algorithm with a pay-your-bid payment rule yields a mechanism whose Price of Anarchy is $O(\alpha)$. In this paper we significantly extend the class of algorithms for which such a result is available by showing that this close connection between approximation ratio on the one hand and Price of Anarchy on the other also holds for the design principle of relaxation and rounding provided that the relaxation is smooth and the rounding is oblivious. #R##N#We demonstrate the far-reaching consequences of our result by showing its implications for sparse packing integer programs, such as multi-unit auctions and generalized matching, for the maximum traveling salesman problem, for combinatorial auctions, and for single source unsplittable flow problems. In all these problems our approach leads to novel simple, near-optimal mechanisms whose Price of Anarchy either matches or beats the performance guarantees of known mechanisms.

Connected through hyperedge HE-1 (induced by source paper "the price of anarchy in auctions"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "simple mechanisms for agents with complements"
    - "the price of anarchy in large games"
    - "on the economic efficiency of the combinatorial clock auction"
    - "on the efficiency of all pay mechanisms"
    - "learning and efficiency in games with dynamic population"
    - "no regret learning in bayesian games"

Connected through hyperedge HE-2 (induced by source paper "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"):
  with members:
    - "makespan minimization via posted prices"
    - "simple mechanisms for subadditive buyers via duality"
    - "combinatorial prophet inequalities"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "the price of anarchy in large games"
    - "online contention resolution schemes"
    - "the invisible hand of dynamic market pricing"
    - "train faster generalize better stability of stochastic gradient descent"

Connected through hyperedge HE-3 (induced by source paper "truthful outcomes from non truthful position auctions"):
  with members:
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "an n to 1 bidder reduction for multi item auctions and its applications"
    - "mechanism design for data science"
    - "combinatorial auctions via posted prices"
    - "the simple economics of approximately optimal auctions"
    - "price of anarchy for greedy auctions"

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)