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 "towards an algebraic network information theory simultaneous joint typicality decoding"):
  Abstract: Consider a receiver in a multi-user network that wishes to decode several messages. Simultaneous joint typicality decoding is one of the most powerful techniques for determining the fundamental limits at which reliable decoding is possible. This technique has historically been used in conjunction with random i.i.d. codebooks to establish achievable rate regions for networks. Recently, it has been shown that, in certain scenarios, nested linear codebooks in conjunction with "single-user" or sequential decoding can yield better achievable rates. For instance, the compute-forward problem examines the scenario of recovering $L \le K$ linear combinations of transmitted codewords over a $K$-user multiple-access channel (MAC), and it is well established that linear codebooks can yield higher rates. Here, we develop bounds for simultaneous joint typicality decoding used in conjunction with nested linear codebooks, and apply them to obtain a larger achievable region for compute-forward over a $K$-user discrete memoryless MAC. The key technical challenge is that competing codeword tuples that are linearly dependent on the true codeword tuple introduce statistical dependencies, which requires careful partitioning of the associated error events.

Includes members:
  Member "homologous codes for multiple access channels":
    also connected through other hyperedges:
      (none)
  Member "gaussian multiple access via compute and forward":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "private information retrieval over gaussian mac")
  Member "polynomially solvable instances of the shortest and closest vector problems with applications to compute and forward":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ring compute and forward over block fading channels")
  Member "an achievable rate region for the three user interference channel based on coset codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "homologous codes for multiple access channels")
  Member "equivalence of additive combinatorial linear inequalities for shannon entropy and differential entropy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "demystifying fixed k nearest neighbor information estimators")
  Member "expanding the compute and forward framework unequal powers signal levels and multiple linear combinations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "compute and forward relaying with ldpc codes over qpsk scheme")
  Member "secure compute and forward in a bidirectional relay":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "secure modulo sum via multiple access channel")
  Member "distributed decode forward for relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul")

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)