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: "new model for rigorous analysis of lt codes"
  Abstract: We present a new model for LT codes which simplifies the analysis of the error probability of decoding by belief propagation. For any given degree distribution, we provide the first rigorous expression for the limiting error probability as the length of the code goes to infinity via recent results in random hypergraphs [Darling-Norris 2005]. For a code of finite length, we provide an algorithm for computing the probability of error of the decoder. This algorithm improves the one of [Karp-Luby-Shokrollahi 2004] by a linear factor.

Connected through hyperedge HE-1 (induced by source paper "inactivation decoding of lt and raptor codes analysis and code design"):
  with members:
    - "bounds on the error probability of raptor codes"
    - "distance spectrum of fixed rate raptor codes with linear random precoders"
    - "inactivation decoding analysis for lt codes"
    - "lt code design for inactivation decoding"
    - "distributed raptor coding for erasure channels partially and fully coded cooperation"
    - "analysis of the second moment of the lt decoder"
    - "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding"

Connected through hyperedge HE-2 (induced by source paper "finite length analysis of bats codes"):
  with members:
    - "inactivation decoding analysis for lt codes"
    - "lt code design for inactivation decoding"
    - "batched sparse codes"
    - "on coding for reliable communication over packet networks"

Connected through hyperedge HE-3 (induced by source paper "design and analysis of lt codes with decreasing ripple size"):
  with members:
    - "analysis of the second moment of the lt decoder"
    - "intermediate performance of rateless codes"

Connected through hyperedge HE-4 (induced by source paper "doped fountain coding for minimum delay data collection in circular networks"):
  with members:
    - "decentralized coding algorithms for distributed storage in wireless sensor networks"
    - "decentralized erasure codes for distributed networked storage"

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)