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: "information complexity is computable"
  Abstract: The information complexity of a function $f$ is the minimum amount of information Alice and Bob need to exchange to compute the function $f$. In this paper we provide an algorithm for approximating the information complexity of an arbitrary function $f$ to within any additive error $\alpha > 0$, thus resolving an open question as to whether information complexity is computable. #R##N#In the process, we give the first explicit upper bound on the rate of convergence of the information complexity of $f$ when restricted to $b$-bit protocols to the (unrestricted) information complexity of $f$.

Connected through hyperedge HE-1 (induced by source paper "information complexity of the and function in the two party and multiparty settings"):
  with members:
    - "trading information complexity for error"
    - "information equals amortized communication"
    - "asymptotically optimal lower bounds on the nih multi party information"
    - "the infinite message limit of two terminal interactive source coding"

Connected through hyperedge HE-2 (induced by source paper "dimension reduction for polynomials over gaussian space and applications"):
  with members:
    - "on the duality of additivity and tensorization"

Connected through hyperedge HE-3 (induced by source paper "on the public communication needed to achieve sk capacity in the multiterminal source model"):
  with members:
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "the communication complexity of achieving sk capacity in a class of pin models"
    - "achieving sk capacity in the source model when must all terminals talk"
    - "coded cooperative data exchange for a secret key"
    - "on the communication complexity of secret key generation in the multiterminal source model"
    - "wyner s common information generalizations and a new lossy source coding interpretation"
    - "outer bounds for multiterminal source coding via a strong data processing inequality"
    - "common information and secret key capacity"

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"
    - "on the duality of additivity and tensorization"
    - "on non interactive simulation of joint distributions"
    - "communication complexity of permutation invariant functions"
    - "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 "lower bounds for interactive function computation via wyner common information"):
  with members:
    - "assisted common information with an application to secure two party sampling"
    - "a new upperbound for the oblivious transfer capacity of discrete memoryless channels"
    - "tension bounds for information complexity"
    - "the infinite message limit of two terminal interactive source coding"

Connected through hyperedge HE-6 (induced by source paper "trading information complexity for error"):
  with members:
    - "information equals amortized communication"

Connected through hyperedge HE-7 (induced by source paper "communication complexity of permutation invariant functions"):
  with members:
    - "on the role of shared randomness in simultaneous communication"
    - "communication with imperfectly shared randomness"
    - "on the communication complexity of sparse set disjointness and exists equal problems"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "on extracting common random bits from correlated sources on large alphabets"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "on extracting common random bits from correlated sources"
    - "the partition bound for classical communication complexity and query 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.IT(Information Theory)