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: "lt code design for inactivation decoding"
  Abstract: We present a simple model of inactivation decoding for LT codes which can be used to estimate the decoding complexity as a function of the LT code degree distribution. The model is shown to be accurate in variety of settings of practical importance. The proposed method allows to perform a numerical optimization on the degree distribution of a LT code aiming at minimizing the number of inactivations required for decoding.

Connected through hyperedge HE-1 (induced by source paper "bounds on the error probability of raptor codes under maximum likelihood decoding"):
  with members:
    - "fountain codes under maximum likelihood decoding"
    - "bounds on the error probability of raptor codes"
    - "distance spectrum of fixed rate raptor codes with linear random precoders"
    - "on the weight distribution of fixed rate raptor codes"
    - "inactivation decoding analysis for lt codes"

Connected through hyperedge HE-2 (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"
    - "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"
    - "new model for rigorous analysis of lt codes"

Connected through hyperedge HE-3 (induced by source paper "block diagonal and lt codes for distributed computing with straggling servers"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "block diagonal coding for distributed computing with straggling servers"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "a unified coding framework for distributed computing with straggling servers"
    - "using straggler replication to reduce latency in large scale parallel computing"

Connected through hyperedge HE-4 (induced by source paper "bounds on the error probability of raptor codes"):
  with members:
    - "distance spectrum of fixed rate raptor codes with linear random precoders"
    - "on the weight distribution of fixed rate raptor codes"
    - "inactivation decoding analysis for lt codes"

Connected through hyperedge HE-5 (induced by source paper "distance spectrum of fixed rate raptor codes with linear random precoders"):
  with members:
    - "on the weight distribution of fixed rate raptor codes"
    - "performance analysis of raptor codes under maximum likelihood ml decoding"
    - "protograph based raptor like ldpc codes"

Connected through hyperedge HE-6 (induced by source paper "inactivation decoding analysis for lt codes"):
  with members:
    - "finite length analysis of bats codes"
    - "analysis of the second moment of the lt decoder"

Connected through hyperedge HE-7 (induced by source paper "finite length analysis of bats codes"):
  with members:
    - "inactivation decoding analysis for lt codes"
    - "batched sparse codes"
    - "on coding for reliable communication over packet networks"
    - "new model for rigorous analysis of lt codes"

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)