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: "gaussian belief propagation based multiuser detection"
  Abstract: In this work, we present a novel construction for solving the linear multiuser detection problem using the Gaussian Belief Propagation algorithm. Our algorithm yields an efficient, iterative and distributed implementation of the MMSE detector. Compared to our previous formulation, the new algorithm offers a reduction in memory requirements, the number of computational steps, and the number of messages passed. We prove that a detection method recently proposed by Montanari et al. is an instance of ours, and we provide new convergence results applicable to both.

Connected through hyperedge HE-1 (induced by source paper "fixed symbol aided random access scheme for machine to machine communications"):
  with members:
    - "deep learning methods for improved decoding of linear codes"
    - "sparse message passing based preamble estimation for crowded m2m communications"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "irregular repetition slotted aloha over the rayleigh block fading channel with capture"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"

Connected through hyperedge HE-2 (induced by source paper "convergence and density evolution of a low complexity mimo detector based on forward backward recursion over a ring"):
  with members:
    - "belief propagation based decoding of large non orthogonal stbcs"
    - "mimo decoding based on stochastic reconstruction from multiple projections"
    - "belief propagation based multi user detection"

Connected through hyperedge HE-3 (induced by source paper "scalable uplink signal detection in c rans via randomized gaussian message passing"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "distributed clock skew and offset estimation in wireless sensor networks asynchronous algorithm and convergence analysis"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "large scale convex optimization for dense wireless cooperative networks"
    - "a low complexity gaussian message passing iterative detector for massive mu mimo systems"
    - "dynamic nested clustering for parallel phy layer processing in cloud rans"
    - "residual belief propagation informed scheduling for asynchronous message passing"
    - "fundamental limits of cooperation"

Connected through hyperedge HE-4 (induced by source paper "performing bayesian risk aggregation using discrete approximation algorithms with graph factorization"):
  with members:
    - "learning bayesian networks with local structure"
    - "expectation propagation for approximate bayesian inference"
    - "generalized belief propagation on tree robust structured region graphs"
    - "on the choice of regions for generalized belief propagation"
    - "structured region graphs morphing ep into gbp"
    - "convergent message passing algorithms a unifying view"
    - "join graph propagation algorithms"
    - "truncating the loop series expansion for belief propagation"

Connected through hyperedge HE-5 (induced by source paper "low complexity mimo detection based on belief propagation over pair wise graphs"):
  with members:
    - "mimo decoding based on stochastic reconstruction from multiple projections"
    - "belief propagation based multi user detection"

Connected through hyperedge HE-6 (induced by source paper "generating functional analysis for iterative cdma multiuser detectors"):
  with members:
    - "the dynamics of message passing on dense graphs with applications to compressed sensing"
    - "message passing algorithms for compressed sensing"
    - "microscopic analysis for decoupling principle of linear vector channel"
    - "vector precoding for wireless mimo systems and its replica analysis"
    - "randomly spread cdma asymptotics via statistical physics"

Connected through hyperedge HE-7 (induced by source paper "mimo detection for high order qam based on a gaussian tree approximation"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "the equivalence of semidefinite relaxation mimo detectors for higher order qam"
    - "improved message passing for inference in densely connected systems"
    - "belief propagation based multi user detection"

Connected through hyperedge HE-8 (induced by source paper "inference with multivariate heavy tails in linear models"):
  with members:
    - "expectation propagation for approximate bayesian inference"
    - "convolutional factor graphs as probabilistic models"
    - "gaussian belief propagation theory and application"

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)