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: "welfare maximization with limited interaction"
  Abstract: We continue the study of welfare maximization in unit-demand (matching) markets, in a distributed information model where agent's valuations are unknown to the central planner, and therefore communication is required to determine an efficient allocation. Dobzinski, Nisan and Oren (STOC'14) showed that if the market size is $n$, then $r$ rounds of interaction (with logarithmic bandwidth) suffice to obtain an $n^{1/(r+1)}$-approximation to the optimal social welfare. In particular, this implies that such markets converge to a stable state (constant approximation) in time logarithmic in the market size. #R##N#We obtain the first multi-round lower bound for this setup. We show that even if the allowable per-round bandwidth of each agent is $n^{\epsilon(r)}$, the approximation ratio of any $r$-round (randomized) protocol is no better than $\Omega(n^{1/5^{r+1}})$, implying an $\Omega(\log \log n)$ lower bound on the rate of convergence of the market to equilibrium. #R##N#Our construction and technique may be of interest to round-communication tradeoffs in the more general setting of combinatorial auctions, for which the only known lower bound is for simultaneous ($r=1$) protocols [DNO14].

Connected through hyperedge HE-1 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms"):
  with members:
    - "smaller cuts higher lower bounds"
    - "parallelization does not accelerate convex optimization adaptivity lower bounds for non smooth convex minimization"
    - "an exponential speedup in parallel running time for submodular maximization without loss in approximation"
    - "non monotone submodular maximization with nearly optimal adaptivity complexity"
    - "submodular maximization with optimal approximation adaptivity and query complexity"
    - "tight bounds on the round complexity of the distributed maximum coverage problem"
    - "non monotone submodular maximization in exponentially fewer iterations"
    - "submodular maximization with nearly optimal approximation and adaptivity in nearly linear time"

Connected through hyperedge HE-2 (induced by source paper "communication distortion and randomness in metric voting"):
  with members:
    - "comparing election methods where each voter ranks only few candidates"
    - "improved metric distortion for deterministic social choice rules"
    - "approval based elections and distortion of voting rules"
    - "an analysis framework for metric voting based on lp duality"
    - "random dictators with a random referee constant sample complexity mechanisms for social choice"
    - "of the people voting is more effective with representative candidates"
    - "on the distortion of voting with multiple representative candidates"
    - "combinatorial auctions do need modest interaction"

Connected through hyperedge HE-3 (induced by source paper "the demand query model for bipartite matching"):
  with members:
    - "economic efficiency requires interaction"
    - "navigating central path with electrical flows from flows to matchings and back"

Connected through hyperedge HE-4 (induced by source paper "tight bounds on the round complexity of the distributed maximum coverage problem"):
  with members:
    - "distributed partial clustering"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "on estimating maximum matching size in graph streams"
    - "combinatorial auctions do need modest interaction"
    - "submodular optimization over sliding windows"
    - "distributed coverage maximization via sketching"
    - "almost optimal streaming algorithms for coverage problems"
    - "better streaming algorithms for the maximum coverage problem"

Connected through hyperedge HE-5 (induced by source paper "an exponential speedup in parallel running time for submodular maximization without loss in approximation"):
  with members:
    - "an adaptivity hierarchy theorem for property testing"
    - "settling the query complexity of non adaptive junta testing"
    - "parallel algorithms for select and partition with noisy comparisons"
    - "the power of randomization distributed submodular maximization on massive datasets"
    - "noisy submodular maximization via adaptive sampling with applications to crowdsourced image collection summarization"
    - "locally adaptive optimization adaptive seeding for monotone submodular functions"
    - "lazier than lazy greedy"
    - "the non adaptive query complexity of testing k parities"

Connected through hyperedge HE-6 (induced by source paper "complement free couples must communicate a hardness result for two player combinatorial auctions"):
  with members:
    - "combinatorial auctions do need modest interaction"
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "a unifying hierarchy of valuations with complements and substitutes"
    - "the computational complexity of truthfulness in combinatorial auctions"
    - "information equals amortized communication"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"

Connected through hyperedge HE-7 (induced by source paper "communication complexity of cake cutting"):
  with members:
    - "consensus halving is ppa complete"
    - "the query complexity of cake cutting"
    - "combinatorial auctions do need modest interaction"
    - "a discrete and bounded envy free cake cutting protocol for any number of agents"
    - "waste makes haste bounded time algorithms for envy free cake cutting with free disposal"
    - "hardness results for consensus halving"
    - "communication complexity for algorithm designers"
    - "a stable marriage requires communication"

Connected through hyperedge HE-8 (induced by source paper "communication complexity of approximate maximum matching in the message passing model"):
  with members:
    - "maximum matching in turnstile streams"
    - "economic efficiency requires interaction"
    - "when distributed computation is communication expensive"
    - "better bounds for matchings in the streaming model"
    - "laminar families and metric embeddings non bipartite maximum matching problem in the semi streaming model"
    - "maximum matching in semi streaming with few passes"
    - "sorting searching and simulation in the mapreduce framework"
    - "improved approximation guarantees for weighted matching in the semi streaming model"

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)