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: "communication complexity of permutation invariant functions"
  Abstract: Motivated by the quest for a broader understanding of communication complexity of simple functions, we introduce the class of "permutation-invariant" functions. A partial function $f:\{0,1\}^n \times \{0,1\}^n\to \{0,1,?\}$ is permutation-invariant if for every bijection $\pi:\{1,\ldots,n\} \to \{1,\ldots,n\}$ and every $\mathbf{x}, \mathbf{y} \in \{0,1\}^n$, it is the case that $f(\mathbf{x}, \mathbf{y}) = f(\mathbf{x}^{\pi}, \mathbf{y}^{\pi})$. Most of the commonly studied functions in communication complexity are permutation-invariant. For such functions, we present a simple complexity measure (computable in time polynomial in $n$ given an implicit description of $f$) that describes their communication complexity up to polynomial factors and up to an additive error that is logarithmic in the input size. This gives a coarse taxonomy of the communication complexity of simple functions. Our work highlights the role of the well-known lower bounds of functions such as 'Set-Disjointness' and 'Indexing', while complementing them with the relatively lesser-known upper bounds for 'Gap-Inner-Product' (from the sketching literature) and 'Sparse-Gap-Inner-Product' (from the recent work of Canonne et al. [ITCS 2015]). We also present consequences to the study of communication complexity with imperfectly shared randomness where we show that for total permutation-invariant functions, imperfectly shared randomness results in only a polynomial blow-up in communication complexity after an additive $O(\log \log n)$ overhead.

Connected through hyperedge HE-1 (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"
    - "resource efficient common randomness and secret key schemes"
    - "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 with imperfectly shared randomness"
    - "common information and secret key capacity"

Connected through hyperedge HE-2 (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"
    - "resource efficient common randomness and secret key schemes"
    - "decidability of non interactive simulation of joint distributions"
    - "on the role of shared randomness in simultaneous communication"
    - "on non interactive simulation of joint distributions"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "the power of shared randomness in uncertain communication"):
  with members:
    - "communication with contextual uncertainty"
    - "on the role of shared randomness in simultaneous communication"
    - "analysis of boolean functions"

Connected through hyperedge HE-4 (induced by source paper "decidability of non interactive simulation of joint distributions"):
  with members:
    - "on the role of shared randomness in simultaneous communication"
    - "information complexity is computable"
    - "on the duality of additivity and tensorization"
    - "on non interactive simulation of joint distributions"
    - "communication with imperfectly shared randomness"
    - "information equals amortized communication"
    - "reductions between expansion problems"
    - "a regularity lemma and low weight approximators for low degree polynomial threshold functions"

Connected through hyperedge HE-5 (induced by source paper "communication with contextual uncertainty"):
  with members:
    - "the power of shared randomness in uncertain communication"
    - "on the role of shared randomness in simultaneous communication"
    - "communication with imperfectly shared randomness"
    - "deterministic compression with uncertain priors"
    - "information equals amortized communication"
    - "on extracting common random bits from correlated sources"

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)