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 "universality for the noisy slepian wolf problem via spatial coupling"):
  Abstract: We consider a noisy Slepian-Wolf problem where two correlated sources are separately encoded and transmitted over two independent binary memoryless symmetric channels. Each channel capacity is assumed to be characterized by a single parameter which is not known at the transmitter. The receiver has knowledge of both the source correlation and the channel parameters. We call a system universal if it retains near-capacity performance without channel knowledge at the transmitter. Kudekar et al. recently showed that terminated low-density parity-check (LDPC) convolutional codes (a.k.a. spatially-coupled LDPC ensembles) can have belief-propagation thresholds that approach their maximum a-posteriori thresholds. This was proven for binary erasure channels and shown empirically for binary memoryless symmetric channels. They also conjectured that the principle of spatial coupling is very general and the phenomenon of threshold saturation applies to a very broad class of graphical models. In this work, we derive an area theorem for the joint decoder and empirically show that threshold saturation occurs for this problem. As a result, we demonstrate near-universal performance for this problem using the proposed spatially-coupled coding system. A similar result is also discussed briefly for the 2-user multiple-access channel.

Includes members:
  Member "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "ldpc code design for transmission of correlated sources across noisy channels without csit":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatially coupled ldpc codes for decode and forward relaying of two correlated sources over the bec")
  Member "threshold saturation on bms channels via spatial coupling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "systematic convolutional low density generator matrix code")
  Member "can iterative decoding for erasure correlated sources be universal":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asymptotic analysis on ldpc bicm scheme for compute and forward relaying")
  Member "slepian wolf code design via source channel correspondence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "code design for the noisy slepian wolf problem")
  Member "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reed muller codes theory and algorithms")
  Member "the generalized area theorem and some of its consequences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reed muller codes theory and algorithms")
  Member "network information flow with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "capacity bounds for networks with correlated sources and characterisation of distributions by entropies")

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)