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: "on the approximability of budget feasible mechanisms"
  Abstract: Budget feasible mechanisms, recently initiated by Singer (FOCS 2010), extend algorithmic mechanism design problems to a realistic setting with a budget constraint. We consider the problem of designing truthful budget feasible mechanisms for general submodular functions: we give a randomized mechanism with approximation ratio $7.91$ (improving the previous best-known result 112), and a deterministic mechanism with approximation ratio $8.34$. Further we study the knapsack problem, which is special submodular function, give a $2+\sqrt{2}$ approximation deterministic mechanism (improving the previous best-known result 6), and a 3 approximation randomized mechanism. We provide a similar result for an extended knapsack problem with heterogeneous items, where items are divided into groups and one can pick at most one item from each group. #R##N#Finally we show a lower bound of approximation ratio of $1+\sqrt{2}$ for deterministic mechanisms and 2 for randomized mechanisms for knapsack, as well as the general submodular functions. Our lower bounds are unconditional, which do not rely on any computational or complexity assumptions.

Connected through hyperedge HE-1 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online"):
  with members:
    - "a nearly linear time algorithm for submodular maximization with a knapsack constraint"
    - "on budget feasible mechanism design for symmetric submodular objectives"
    - "simple and efficient budget feasible mechanisms for monotone submodular valuations"
    - "greed is good near optimal submodular maximization via greedy optimization"
    - "budget feasible mechanisms on matroids"
    - "adaptivity gaps for stochastic probing submodular and xos functions"
    - "coverage matching and beyond new results on budgeted mechanism design"
    - "submodular secretary problems cardinality matching and linear constraints"

Connected through hyperedge HE-2 (induced by source paper "approximately maximizing the broker s profit in a two sided market"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "approximate revenue maximization with multiple items"
    - "muda a truthful multi unit double auction mechanism"
    - "double auctions in markets for multiple kinds of goods"
    - "approximately efficient two sided combinatorial auctions"
    - "an n to 1 bidder reduction for multi item auctions and its applications"
    - "truthful multi unit procurements with budgets"

Connected through hyperedge HE-3 (induced by source paper "optimal budget feasible mechanisms for additive valuations"):
  with members:
    - "on budget feasible mechanism design for symmetric submodular objectives"
    - "simple and efficient budget feasible mechanisms for monotone submodular valuations"
    - "budget feasible mechanisms on matroids"
    - "coverage matching and beyond new results on budgeted mechanism design"
    - "bayesian budget feasibility with posted pricing"
    - "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets"
    - "budget feasible mechanisms for experimental design"
    - "frugal mechanism design via spectral techniques"

Connected through hyperedge HE-4 (induced by source paper "a simple mechanism for a budget constrained buyer"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "revenue maximization and ex post budget constraints"
    - "the menu size complexity of revenue approximation"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "mixture selection mechanism design and signaling"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-5 (induced by source paper "a bridge between liquid and social welfare in combinatorial auctions with submodular bidders"):
  with members:
    - "a bayesian clearing mechanism for combinatorial auctions"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "bayesian budget feasibility with posted pricing"
    - "combinatorial auctions via posted prices"
    - "budget feasible mechanism design from prior free to bayesian"
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"

Connected through hyperedge HE-6 (induced by source paper "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"):
  with members:
    - "securing the internet of things in the age of machine learning and software defined networking"
    - "quality of information in mobile crowdsensing survey and research challenges"
    - "taskme multi task allocation in mobile crowd sensing"
    - "incentive mechanisms for participatory sensing survey and research challenges"
    - "mining users significant driving routes with low power sensors"
    - "budget feasible mechanisms"

Connected through hyperedge HE-7 (induced by source paper "on budget feasible mechanism design for symmetric submodular objectives"):
  with members:
    - "simple and efficient budget feasible mechanisms for monotone submodular valuations"
    - "budget feasible mechanisms on matroids"
    - "adaptivity gaps for stochastic probing submodular and xos functions"
    - "coverage matching and beyond new results on budgeted mechanism design"
    - "bayesian budget feasibility with posted pricing"
    - "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets"
    - "budget feasible mechanisms for experimental design"
    - "incentives for privacy tradeoff in community sensing"

Connected through hyperedge HE-8 (induced by source paper "simple and efficient budget feasible mechanisms for monotone submodular valuations"):
  with members:
    - "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets"
    - "budget feasible mechanism design from prior free to bayesian"
    - "budget feasible mechanisms"

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)