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: "hash property and fixed rate universal coding theorems"
  Abstract: The aim of this paper is to prove the achievability of fixed-rate universal coding problems by using our previously introduced notion of hash property. These problems are the fixed-rate lossless universal source coding problem and the fixed-rate universal channel coding problem. Since an ensemble of sparse matrices satisfies the hash property requirement, it is proved that we can construct universal codes by using sparse matrices.

Connected through hyperedge HE-1 (induced by source paper "construction of multiple access channel codes based on hash property"):
  with members:
    - "construction of slepian wolf source code and broadcast channel code based on hash property"
    - "lecture notes on network information theory"
    - "hash property and coding theorems for sparse matrices and maximum likelihood coding"

Connected through hyperedge HE-2 (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"
    - "construction of codes for wiretap channel and secret key agreement from correlated source outputs by using sparse matrices"
    - "disjoint ldpc coding for gaussian broadcast channels"
    - "an outer bound for 2 receiver discrete memoryless broadcast channels"
    - "hash property and coding theorems for sparse matrices and maximum likelihood coding"

Connected through hyperedge HE-3 (induced by source paper "construction of codes for wiretap channel and secret key agreement from correlated source outputs by using sparse matrices"):
  with members:
    - "hash property and coding theorems for sparse matrices and maximum likelihood coding"
    - "applications of ldpc codes to the wiretap channel"

Connected through hyperedge HE-4 (induced by source paper "hash property and coding theorems for sparse matrices and maximum likelihood coding"):
  with members:
    - "construction of codes for wiretap channel and secret key agreement from correlated source outputs by using sparse matrices"
    - "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)