human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "convergence of weighted min sum decoding via dynamic programming on trees"):
  Abstract: Applying the max-product (and belief-propagation) algorithms to loopy graphs is now quite popular for best assignment problems. This is largely due to their low computational complexity and impressive performance in practice. Still, there is no general understanding of the conditions required for convergence and/or the optimality of converged solutions. This paper presents an analysis of both attenuated max-product (AMP) decoding and weighted min-sum (WMS) decoding for LDPC codes which guarantees convergence to a fixed point when a weight parameter, {\beta}, is sufficiently small. It also shows that, if the fixed point satisfies some consistency conditions, then it must be both the linear-programming (LP) and maximum-likelihood (ML) solution. #R##N#For (dv,dc)-regular LDPC codes, the weight must satisfy {\beta}(dv-1) \leq 1 whereas the results proposed by Frey and Koetter require instead that {\beta}(dv-1)(dc-1)   1 is also given. Finally, connections are explored with recent work by Arora et al. on the threshold of LP decoding.

Includes members:
  Member "on the optimality of tree reweighted max product message passing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "partial optimality of dual decomposition for map inference in pairwise mrfs")
  Member "lp decoding of regular ldpc codes in memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the admm penalized decoder for ldpc codes")
  Member "probabilistic analysis of linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the admm penalized decoder for ldpc codes")
  Member "sufficient conditions for convergence of the sum product algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "factorized graph representations for semi supervised learning from sparse data")
  Member "on the block error probability of lp decoding of ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "impact of redundant checks on the lp decoding thresholds of ldpc codes")
  Member "bounds on the threshold of linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "impact of redundant checks on the lp decoding thresholds of ldpc codes")

Question: Please tell me which class the source paper 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)