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 "computation in multicast networks function alignment and converse theorems"):
  Abstract: The classical problem in network coding theory considers communication over multicast networks. Multiple transmitters send independent messages to multiple receivers which decode the same set of messages. In this work, computation over multicast networks is considered: each receiver decodes an identical function of the original messages. For a countably infinite class of two-transmitter two-receiver single-hop linear deterministic networks, the computing capacity is characterized for a linear function (modulo-2 sum) of Bernoulli sources. Inspired by the geometric concept of interference alignment in networks, a new achievable coding scheme called function alignment is introduced. A new converse theorem is established that is tighter than cut-set based and genie-aided bounds. Computation (vs. communication) over multicast networks requires additional analysis to account for multiple receivers sharing a network's computational resources. We also develop a network decomposition theorem which identifies elementary parallel subnetworks that can constitute an original network without loss of optimality. The decomposition theorem provides a conceptually-simpler algebraic proof of achievability that generalizes to $L$-transmitter $L$-receiver networks.

Includes members:
  Member "interference alignment in regenerating codes for distributed storage necessity and code constructions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "conditional disclosure of secrets a noise and signal alignment approach")
  Member "two way interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "two way function computation")
  Member "approximate feedback capacity of the gaussian multicast channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two way interference channel capacity how to have the cake and eat it too")
  Member "on network coding for sum networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "linear network coding effects of varying the message dimension on the set of characteristics")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "network coding for computing cut set bounds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "expand and randomize an algebraic approach to secure computation")
  Member "computation alignment capacity approximation without noise accumulation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "expanding the compute and forward framework unequal powers signal levels and multiple linear combinations")
  Member "interference channels with rate limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "capacity results for intermittent x channels with delayed channel state feedback")

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)