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: "construction of codes for wiretap channel and secret key agreement from correlated source outputs by using sparse matrices"
  Abstract: The aim of this paper is to prove coding theorems for the wiretap channel and secret key agreement based on the the notion of a hash property for an ensemble of functions. These theorems imply that codes using sparse matrices can achieve the optimal rate. Furthermore, fixed-r ate universal coding theorems for a wiretap channel and a secret key agreement are also proved.

Connected through hyperedge HE-1 (induced by source paper "construction of slepian wolf source code and broadcast channel code based on hash property"):
  with members:
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "lecture notes on network information theory"
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "disjoint ldpc coding for gaussian broadcast channels"
    - "an outer bound for 2 receiver discrete memoryless broadcast channels"
    - "hash property and fixed rate universal coding theorems"
    - "hash property and coding theorems for sparse matrices and maximum likelihood coding"

Connected through hyperedge HE-2 (induced by source paper "hash property and coding theorems for sparse matrices and maximum likelihood coding"):
  with members:
    - "hash property and fixed rate universal coding theorems"
    - "lower bounds on the rate distortion function of ldgm codes"
    - "lower bounds on the rate distortion function of individual ldgm codes"
    - "low density codes achieve the rate distortion bound"
    - "low density constructions can achieve the wyner ziv and gelfand pinsker bounds"

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)