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: "the extraction and complexity limits of graphical models for linear codes"
  Abstract: Two broad classes of graphical modeling problems for codes can be identified in the literature: constructive and extractive problems. The former class of problems concern the construction of a graphical model in order to define a new code. The latter class of problems concern the extraction of a graphical model for a (fixed) given code. The design of a new low-density parity-check code for some given criteria (e.g. target block length and code rate) is an example of a constructive problem. The determination of a graphical model for a classical linear block code which implies a decoding algorithm with desired performance and complexity characteristics is an example of an extractive problem. This work focuses on extractive graphical model problems and aims to lay out some of the foundations of the theory of such problems for linear codes. #R##N#The primary focus of this work is a study of the space of all graphical models for a (fixed) given code. The tradeoff between cyclic topology and complexity in this space is characterized via the introduction of a new bound: the tree-inducing cut-set bound. The proposed bound provides a more precise characterization of this tradeoff than that which can be obtained using existing tools (e.g. the Cut-Set Bound) and can be viewed as a generalization of the square-root bound for tail-biting trellises to graphical models with arbitrary cyclic topologies. Searching the space of graphical models for a given code is then enabled by introducing a set of basic graphical model transformation operations which are shown to span this space. Finally, heuristics for extracting novel graphical models for linear block codes using these transformations are investigated.

Connected through hyperedge HE-1 (induced by source paper "on pseudocodewords and decision regions of linear programming decoding of hdpc codes"):
  with members:
    - "polytope of correct linear programming decoding and low weight pseudo codewords"
    - "lower bounds on the minimum pseudodistance for linear codes with q ary psk modulation over awgn"
    - "a decomposition theory for binary linear codes"
    - "reducing the error floor"
    - "pseudo codeword analysis of tanner graphs from projective and euclidean planes"
    - "on the minimal pseudo codewords of codes from finite geometries"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"
    - "pseudocodewords of tanner graphs"

Connected through hyperedge HE-2 (induced by source paper "the treewidth of mds and reed muller codes"):
  with members:
    - "on minimal tree realizations of linear codes"
    - "constraint complexity of realizations of linear codes on arbitrary graphs"

Connected through hyperedge HE-3 (induced by source paper "on minimal tree realizations of linear codes"):
  with members:
    - "constraint complexity of realizations of linear codes on arbitrary graphs"
    - "a decomposition theory for binary linear codes"
    - "matroid pathwidth and code trellis complexity"

Connected through hyperedge HE-4 (induced by source paper "constraint complexity of realizations of linear codes on arbitrary graphs"):
  with members:
    - "on minimal tree realizations of linear codes"

Connected through hyperedge HE-5 (induced by source paper "performance of ldpc codes under faulty iterative decoding"):
  with members:
    - "loopy belief propagation as a basis for communication in sensor networks"
    - "the price of certainty waterslide curves and the gap to capacity"
    - "channel coding the road to channel capacity"
    - "tight bounds for ldpc and ldgm codes under map decoding"
    - "capacity achieving ensembles for the binary erasure channel with bounded complexity"
    - "density evolution thresholds and the stability condition for non binary ldpc 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)