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: "the non adaptive query complexity of testing k parities"
  Abstract: We prove tight bounds of Theta(k log k) queries for non-adaptively testing whether a function f:{0,1}^n -> {0,1} is a k-parity or far from any k-parity. The lower bound combines a recent method of Blais, Brody and Matulef [BBM11] to get lower bounds for testing from communication complexity with an Omega(k \log k) lower bound for the one-way communication complexity of k-disjointness.

Connected through hyperedge HE-1 (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"
    - "welfare maximization with limited interaction"
    - "locally adaptive optimization adaptive seeding for monotone submodular functions"
    - "lazier than lazy greedy"

Connected through hyperedge HE-2 (induced by source paper "non monotone submodular maximization in exponentially fewer iterations"):
  with members:
    - "an exponential speedup in parallel running time for submodular maximization without loss in approximation"
    - "submodular maximization with nearly optimal approximation and adaptivity in nearly linear time"
    - "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"
    - "constrained submodular maximization beyond 1 e"
    - "on the power of adaptivity in sparse recovery"
    - "submodular maximization by simulated annealing"

Connected through hyperedge HE-3 (induced by source paper "near log convexity of measured heat in discrete time and consequences"):
  with members:
    - "on the communication complexity of sparse set disjointness and exists equal problems"
    - "spectral norm of symmetric functions"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

Connected through hyperedge HE-4 (induced by source paper "annotations for sparse data streams"):
  with members:
    - "arthur merlin streaming complexity"
    - "practical verified computation with streaming interactive proofs"
    - "verifying computations with streaming interactive proofs"
    - "on arthur merlin games in communication complexity"
    - "streaming graph computations with a helpful advisor"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"
    - "rectangle size bounds and threshold covers in communication complexity"

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.CC(Computational Complexity)