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: "resource efficient common randomness and secret key schemes"
  Abstract: We study common randomness where two parties have access to i.i.d. samples from a known random source, and wish to generate a shared random key using limited (or no) communication with the largest possible probability of agreement. This problem is at the core of secret key generation in cryptography, with connections to communication under uncertainty and locality sensitive hashing. We take the approach of treating correlated sources as a critical resource, and ask whether common randomness can be generated resource-efficiently. #R##N#We consider two notable sources in this setup arising from correlated bits and correlated Gaussians. We design the first explicit schemes that use only a polynomial number of samples (in the key length) so that the players can generate shared keys that agree with constant probability using optimal communication. The best previously known schemes were both non-constructive and used an exponential number of samples. In the amortized setting, we characterize the largest achievable ratio of key length to communication in terms of the external and internal information costs, two well-studied quantities in theoretical computer science. In the relaxed setting where the two parties merely wish to improve the correlation between the generated keys of length $k$, we show that there are no interactive protocols using $o(k)$ bits of communication having agreement probability even as small as $2^{-o(k)}$. For the related communication problem where the players wish to compute a joint function $f$ of their inputs using i.i.d. samples from a known source, we give a zero-communication protocol using $2^{O(c)}$ bits where $c$ is the interactive randomized public-coin communication complexity of $f$. This matches the lower bound shown previously while the best previously known upper bound was doubly exponential in $c$.

Connected through hyperedge HE-1 (induced by source paper "communication for generating correlation a unifying survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact exponent for soft covering"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"
    - "strong functional representation lemma and applications to coding theorems"

Connected through hyperedge HE-2 (induced by source paper "round complexity of common randomness generation the amortized setting"):
  with members:
    - "communication rounds tradeoffs for common randomness and secret key generation"
    - "the power of shared randomness in uncertain communication"
    - "secret key generation with limited interaction"
    - "on the role of shared randomness in simultaneous communication"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "communication complexity of permutation invariant functions"
    - "communication with imperfectly shared randomness"
    - "common information and secret key capacity"

Connected through hyperedge HE-3 (induced by source paper "optimal communication rates and combinatorial properties for distributed simulation"):
  with members:
    - "domain compression and its application to randomness optimal distributed goodness of fit"
    - "geometric lower bounds for distributed parameter estimation under communication constraints"
    - "coordination using individually shared randomness"
    - "distributed simulation and distributed inference"
    - "inference under information constraints i lower bounds from chi square contraction"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "communication lower bounds for statistical estimation problems via a distributed data processing inequality"
    - "strong coordination over multi hop line networks"

Connected through hyperedge HE-4 (induced by source paper "communication rounds tradeoffs for common randomness and secret key generation"):
  with members:
    - "dimension reduction for polynomials over gaussian space and applications"
    - "decidability of non interactive simulation of joint distributions"
    - "on the role of shared randomness in simultaneous communication"
    - "on non interactive simulation of joint distributions"
    - "communication complexity of permutation invariant functions"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "common information and secret key capacity"
    - "on extracting common random bits from correlated sources on large alphabets"

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)